| 1. |
- Andreotti, Eleonora, 1988, et al.
(författare)
-
Mathematical Definitions of Scene and Scenario for Analysis of Automated Driving Systems in Mixed-Traffic Simulations
- 2021
-
Ingår i: IEEE Transactions on Intelligent Vehicles. - 2379-8858. ; 6:2, s. 366-375
-
Tidskriftsartikel (refereegranskat)abstract
- This paper introduces a unified mathematical definition for describing commonly used terms encountered in systematical analysis of automated driving systems in mixed-traffic simulations. The most significant contribution of this work is in translating the terms that are clarified previously in literature into a mathematical set and function based format. Our work can be seen as an incremental step towards further formalisation of Domain-Specific-Language (DSL) for scenario representation. We also extended the previous work in the literature to allow more complex scenarios by expanding the model-incompliant information using set-theory to represent the perception capacity of the road-user agents. With this dynamic perception definition, we also support interactive scenarios and are not limited to reactive and pre-defined agent behavior. Our main focus is to give a framework to represent realistic road-user behavior to be used in simulation or computational tool to examine interaction patterns in mixed-traffic conditions. We believe that, by formalising the verbose definitions and extending the previous work in DSL, we can support automatic scenario generation and dynamic/evolving agent behavior models for simulating mixed traffic situations and scenarios. In addition, we can obtain scenarios that are realistic but also can represent rare-conditions that are difficult to extract from field-tests and real driving data repositories.
|
|
| 2. |
- Andreotti, Eleonora, 1988, et al.
(författare)
-
Potential impact of autonomous vehicles in mixed traffic from simulation using real traffic flow
- 2023
-
Ingår i: Journal of Intelligent and Connected Vehicles. - 2399-9802. ; 6:1, s. 1-15
-
Tidskriftsartikel (refereegranskat)abstract
- This work focuses on the potential impacts of the autonomous vehicles in a mixed traffic condition represented in traffic simulator Simulation of Urban MObility (SUMO) with real traffic flow. Specifically, real traffic flow and speed data collected in 2002 and 2019 in Gothenburg were used to simulate daily flow variation in SUMO. In order to predict the most likely drawbacks during the transition from a traffic consisting only manually driven vehicles to a traffic consisting only fully-autonomous vehicles, this study focuses on mixed traffic with different percentages of autonomous and manually driven vehicles. To realize this aim, several parameters of the car following and lane change models of autonomous vehicles are investigated in this paper. Along with the fundamental diagram, the number of lane changes and the number of conflicts are analyzed and studied as measures for improving road safety and efficiency. The study highlights that the autonomous vehicles' features that improve safety and efficiency in 100% autonomous and mixed traffic are different, and the ability of autonomous vehicles to switch between mixed and autonomous driving styles, and vice versa depending on the scenario, is necessary.
|
|
| 3. |
- Andreotti, Eleonora, 1988, et al.
(författare)
-
Safety-centred analysis of transition stages to traffic with fully autonomous vehicles
- 2020
-
Ingår i: IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC.
-
Konferensbidrag (refereegranskat)abstract
- The aim of this paper is to highlight and investigate the effects of increasing presence rate of autonomous vehicles (AVs) in terms of traffic safety and traffic flow characteristics. For this purpose, using existing driver models in traffic simulator software SUMO we identify and analyze those parameters that characterize and distinguish AVs' driving from manual driving in a heterogeneous traffic context. While it is essential to identify the parameters for traffic flow characteristics of heterogeneous fleets compared to homogeneous ones comprising manually driven vehicles (MV) only (i.e. current status), the safety aspects must be also accounted for. In order to combine these two fundamental aspects of heterogeneous traffic, we used a complete description of a highway driving scenario. The scenario integrates the perceptions of different type of vehicles (i.e. AV and MV) involved and the reaction times of human drivers and decision-making units of autonomous vehicles, to explore the impact of both the rate of AV presence and the perturbation in perception capabilities in highway scenarios.
|
|
| 4. |
- Andreotti, Eleonora, 1988, et al.
(författare)
-
Simulation-based impact projection of autonomous vehicle deployment using real traffic flow
- 2021
-
Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- In this work we focus on future projected impacts of the autonomous vehicles in a realistic condition representing mixed traffic. By using real flow and speed data collected in 2002 and 2019 in the city of Gothenburg, we replicated and simulated the daily flow variation in SUMO. The expansion of the city in recent years was reflected in an increase in road users, and it is reasonable to expect it will increase further. Through simulations, it was possible to project this increase and to predict how this will impact the traffic in future. Furthermore, the composition of vehicle types in the future traffic can be expected to change through the introduction of autonomous vehicles. In order to predict the most likely drawbacks during the transition from a traffic consisting only manually driven vehicles to a traffic consisting only fully-autonomous vehicles, we focus on mixed traffic with different percentages of autonomous and manually driven vehicles. To realize this aim, several parameters of the car following and lane change models of autonomous vehicles are investigated in this paper. Along with the fundamental diagram, the number of lane changes and the number of conflicts are analyzed and studied as measures for improving road safety and efficiency.
|
|
| 5. |
- Bayraktar, Ertugrul, et al.
(författare)
-
A hybrid image dataset toward bridging the gap between real and simulation environments for robotics
- 2019
-
Ingår i: Machine Vision and Applications. - : Springer Science and Business Media LLC. - 1432-1769 .- 0932-8092. ; 30:1, s. 23-40
-
Tidskriftsartikel (refereegranskat)abstract
- The primary motivation of computer vision in the robotics field is to obtain a perception level that is as close as possible to human visual system. To achieve this, the inclusion of large datasets is necessary, sometimes involving less-frequent and seemingly irrelevant data to increase the system robustness. To minimize the effort and time in forming such extensive datasets from real world, the preferred method is to utilize simulation environments, replicating real-world conditions as much as possible. Following this solution path, the machine vision problems in robotics (i.e., object detection, recognition, and manipulation) often employ synthetic images in datasets and, however, do not mix them with real-world images. When the systems are trained only using the synthetic images and tested within the simulated world, the tasks requiring object recognition in robotics can be accomplished. However, the systems trained using this procedure cannot be directly used in the real-world experiments or end-user products due to the inconsistencies between real and simulation environments. Therefore, we propose a hybrid image dataset including annotated desktop objects from real and synthetic worlds (ADORESet). This hybrid dataset provides purposeful object categories with a sufficient number of real and synthetic images. ADORESet is composed of colored images with the dimension of 300×300 pixels within 30 categories. Each class has 2500 real-world images acquired from the wild web and 750 synthetic images that are generated within Gazebo simulation environment. This hybrid dataset enables researchers to implement their own algorithms for both real-world and simulation environment conditions. ADORESet is composed of fully annotated object images. The limits of objects are manually specified, and the bounding box coordinates are provided. The successor objects are also labeled to give statistical information and the likelihood about the relations of the objects within the dataset. To further demonstrate the benefits of this dataset, it is tested in object recognition tasks by fine-tuning the state-of-the-art deep convolutional neural networks such as VGGNet, InceptionV3, ResNet, and Xception. The possible combinations regarding the data types for these models are compared in terms of time, accuracy, and loss values. As a result of the conducted object recognition experiments, training with all-real images yields approximately 49% validation accuracy for simulation images. When the training is performed with all-synthetic images and validated using all-real images, the accuracy becomes lower than 10%. If the complete ADORESet is employed for training and validation, the hybrid dataset validation accuracy reaches approximately to 95%. This result proves further that including the real and synthetic images together in the training and validation sessions increases the overall system accuracy and reliability.
|
|
| 6. |
- Bayraktar, Ertugrul, et al.
(författare)
-
Analysis of feature detector and descriptor combinations with a localization experiment for various performance metrics
- 2017
-
Ingår i: Turkish Journal of Electrical Engineering and Computer Sciences. - : The Scientific and Technological Research Council of Turkey (TUBITAK-ULAKBIM) - DIGITAL COMMONS JOURNALS. - 1300-0632 .- 1303-6203. ; 25
-
Tidskriftsartikel (refereegranskat)abstract
- The purpose of this study is to give a detailed performance comparison about the feature detector and descriptor methods, particularly when their various combinations are used for image matching. As the case study, the localization experiments of a mobile robot in an indoor environment are given. In these experiments, 3090 query images and 127 dataset images are used. This study includes five methods for feature detectors such as features from accelerated segment test (FAST), oriented FAST and rotated binary robust independent elementary features (BRIEF) (ORB), speeded-up robust features (SURF), scale invariant feature transform (SIFT), binary robust invariant scalable keypoints (BRISK), and five other methods for feature descriptors which are BRIEF, BRISK, SIFT, SURF, and ORB. These methods are used in 23 different combinations and it was possible to obtain meaningful and consistent comparison results using some performance criteria defined in this study. All of these methods are used independently and separately from each other as being feature detector or descriptor. The performance analysis shows the discriminative power of various combinations of detector and descriptor methods. The analysis is completed using five parameters such as (i) accuracy, (ii) time, (iii) angle difference between keypoints, (iv) number of correct matches, and (v) distance between correctly matched keypoints. In a range of 60°, covering five rotational pose points for our system, FAST-SURF combination gave the best results with the lowest distance and angle difference values and highest number of matched keypoints. The combination SIFT-SURF is obtained as the most accurate combination with 98.41% of correct classification rate. The fastest algorithm is achieved with ?ORB-BRIEF? combination with a total running time 21303.30 seconds in order to match 560 images captured during the motion with 127 dataset images.
|
|
| 7. |
- Bayraktar, Ertugrul, et al.
(författare)
-
Object manipulation with a variable-stiffness robotic mechanism using deep neural networks for visual semantics and load estimation
- 2020
-
Ingår i: Neural Computing and Applications. - : Springer Science and Business Media LLC. - 0941-0643 .- 1433-3058. ; 32:13, s. 9029-9045
-
Tidskriftsartikel (refereegranskat)abstract
- In recent years, the computer vision applications in the robotics have been improved to approach human-like visual perception and scene/context understanding. Following this aspiration, in this study, we explored the possibility of better object manipulation performance by connecting the visual recognition of objects to their physical attributes, such as weight and center of gravity (CoG). To develop and test this idea, an object manipulation platform is built comprising a robotic arm, a depth camera fixed at the top center of the workspace, embedded encoders in the robotic arm mechanism, and microcontrollers for position and force control. Since both the visual recognition and force estimation algorithms use deep learning principles, the test set-up was named as Deep-Table. The objects in the manipulation tests are selected from everyday life and are common to be seen on modern office desktops. The visual object localization and recognition processes are performed from two distinct branches by deep convolutional neural network architectures. We present five of the possible cases, having different levels of information availability on the object weight and CoG in the experiments. The results confirm that using our algorithm, the robotic arm can move different types of objects successfully varying from several grams (empty bottle) to around 250 g (ceramic cup) without failure or tipping. The proposed method also shows that connecting the object recognition with load estimation and contact point further improves the performance characterized by a smoother motion.
|
|
| 8. |
- Boyraz Baykas, Pinar, 1981
(författare)
-
Acoustic road-type estimation for intelligent vehicle safety applications
- 2014
-
Ingår i: International Journal of Vehicle Safety. - 1479-3105 .- 1479-3113. ; 7:2, s. 209-222
-
Tidskriftsartikel (refereegranskat)abstract
- A low-cost acoustic road-type classification system is proposed to be used in road-tyre friction force estimation in active safety applications. The system employs audio signal processing and extracts features such as linear predictive coefficients (LPC), mel-frequency cepstrum coefficients (MFCC) and power spectrum coefficients (PSC). The features are extracted using time windows of 0.02, 0.05 and 0.1 seconds in order to find the best representative window for the signal properties which should also be as short as possible for active safety systems. In order to find the best feature space, a variance analysis based approach is considered to represent the road types as distinguished classes. Optimised feature space is classified using artificial neural networks (ANN). The results show that the designed ANN can classify the road types with 91% accuracy at worst condition. To demonstrate the value of the system, a case study including traction control application is reported.
|
|
| 9. |
- Boyraz Baykas, Pinar, 1981, et al.
(författare)
-
Active Accident Avoidance Case Study: Integrating Drowsiness Monitoring System with Lateral Control and Speed Regulation in Passenger Vehicles
- 2008
-
Ingår i: IEEE International Conference on Vehicular Electronics and Safety. - 9781424423590 ; , s. 293-298
-
Konferensbidrag (refereegranskat)abstract
- This study proposes architecture for integrating intelligent control systems into vehicles, with special consideration to include the human-driver in the control loop. As a case study of the proposed architecture, drowsiness monitoring system is combined with an adaptive and robust lateral controller. Drowsiness is considered to be related to the uncertainty in steering wheel commands for the vehicle lateral movement. Using a robust control theory scheme, the uncertainties from road-vehicle forces and driver inputs are addressed resulting in a lateral controller. The controller is able to re-shape the frequency response of the vehicle in both lateral acceleration and side-slip angle, shifting the response into more stable areas in Nyquist diagram. An additional speed reduction finalizes the complete stabilization of the vehicle-driver system. The stabilization in lateral dynamics of the car and speed reduction addresses the characteristics of the road accident patterns including drowsy/sleepy drivers.
|
|
| 10. |
- Boyraz Baykas, Pinar, 1981, et al.
(författare)
-
Active vehicle safety system design based on driver characteristics and behaviour
- 2009
-
Ingår i: International Journal of Vehicle Safety. - 1479-3105 .- 1479-3113. ; 4:4, s. 330-364
-
Tidskriftsartikel (refereegranskat)abstract
- In the development of driver adaptive and context aware active safety applications, driver-vehicle interaction signals offer excellent opportunities for advanced system design, yet limited progress has been realised. The implementation of driver adaptive and context aware systems requires longer time windows to analyse the current status of the driver and/or traffic situation ahead. In this study, a summary of systems that can be realised based on the long-term analysis of driver-vehicle interaction signals is presented. These signals are readily obtained by using Controller Area Network (CAN) Bus via On Board Diagnostic System (OBD) II port that can be utilised at low cost. Based on the analysis results, quantitative metrics are suggested that can be used in many ways, with two prospects considered here: (1) manoeuvres can be recognised for context aware intelligent active safety and (2) the models or signal processing methods can be proposed so as to distinguish distracted/impaired driver behaviour from normal/safe behaviour.
|
|
| 11. |
- Boyraz Baykas, Pinar, 1981, et al.
(författare)
-
An overview of novel actuators for soft robotics
- 2018
-
Ingår i: Actuators. - : MDPI AG. - 2076-0825. ; 7:3
-
Forskningsöversikt (refereegranskat)abstract
- In this systematic survey, an overview of non-conventional actuators particularly used in soft-robotics is presented. The review is performed by using well-defined performance criteria with a direction to identify the exemplary and potential applications. In addition to this, initial guidelines to compare the performance and applicability of these novel actuators are provided. The meta-analysis is restricted to five main types of actuators: shape memory alloys (SMAs), fluidic elastomer actuators (FEAs), shape morphing polymers (SMPs), dielectric electro-activated polymers (DEAPs), and magnetic/electro-magnetic actuators (E/MAs). In exploring and comparing the capabilities of these actuators, the focus was on eight different aspects: compliance, topology-geometry, scalability-complexity, energy efficiency, operation range, modality, controllability, and technological readiness level (TRL). The overview presented here provides a state-of-the-art summary of the advancements and can help researchers to select the most convenient soft actuators using the comprehensive comparison of the suggested quantitative and qualitative criteria.
|
|
| 12. |
- Boyraz Baykas, Pinar, 1981, et al.
(författare)
-
Design of a Low-cost Tactile Robotic Sleeve for Autonomous Endoscopes and Catheters
- 2020
-
Ingår i: Measurement and Control. - : SAGE Publications. - 0020-2940. ; 53:3-4, s. 613-626
-
Tidskriftsartikel (refereegranskat)abstract
- Recent developments in medical robotics have been significant, supporting the minimally invasive operation requirements, such as smaller devices and more feedback available to surgeons. Nevertheless, the tactile feedback from a catheter or endoscopic type robotic device has been restricted mostly on the tip of the device and was not aimed to support the autonomous movement of the medical device during operation. In this work, we design a robotic sheath/sleeve with a novel and more comprehensive approach, which can function for whole-body or segment-based feedback control as well as diagnostic purposes. The robotic sleeve has several types of piezo-resistive pressure and extension sensors, which are embedded at several latitudes and depths of the silicone substrate. The sleeve takes the human skin as a biological model for its structure. It has a better tactile sensation of the inner tissues in the torturous narrow channels such as cardiovascular or endo-luminal tracts in human body thus can be used to diagnose abnormalities. In addition to this capability, using the stretch sensors distributed alongside its body, the robotic sheath/sleeve can perceive the ego-motion of the robotic backbone of the catheter and can act as a position feedback device. Because of the silicone substrate, the sleeve contributes toward safety of the medical device passively by providing a compliant interface. As an active safety measure, the robotic sheath can sense blood-clots or sudden turns inside a channel and by modifying the local trajectory, and can prevent embolisms or tissue rupture. In the future, advanced manufacturing techniques will increase the capabilities of the tactile robotic sleeve.
|
|
| 13. |
- Boyraz Baykas, Pinar, 1981, et al.
(författare)
-
Dynamic Modeling of a Horizontal Washing Machine and Optimization of Vibration Characteristics using Genetic Algorithms
- 2013
-
Ingår i: Mechatronics. - : Elsevier BV. - 0957-4158. ; 23:6, s. 581-593
-
Tidskriftsartikel (refereegranskat)abstract
- In this work, a 2D dynamic model of a horizontal axis washing machine is derived regarding the rotation plane in order to examine the vibration characteristics of the spin-cycle and improve the design proposing a new optimization scheme based on Genetic Algorithms (GA). The dynamic model is numerically simulated and the outputs are validated using experimental vibration data acquired from a test-rig including the drum and the motor of a horizontal-axis washing machine. The measurements are performed using piezo-transducers and a novel measurement scheme is used to obtain displacement values from acceleration data as well as estimating the instantaneous frequency of the rotation with appropriate signal processing. This study has two main contributions: (i) a new method for design improvement applying GA to optimization of vibration characteristics for the horizontal-axis washing machines, and (ii) a novel measurement method yielding the displacement in 2D and instantaneous frequency of vibration from acceleration data. While the GA is contributing to passive improvement methods in the field, the novel measurement method opens the way for low-cost diagnosis and active-vibration control of washing machines.
|
|
| 14. |
- Boyraz Baykas, Pinar, 1981, et al.
(författare)
-
Multi-sensor Driver Drowsiness Monitoring
- 2008
-
Ingår i: Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering. - 2041-2991 .- 0954-4070. ; 222:11, s. 2041-2062
-
Tidskriftsartikel (refereegranskat)abstract
- A system for driver drowsiness monitoring is proposed, using multi-sensor dataacquisition and investigating two decision-making algorithms, namely a fuzzy inference system(FIS) and an artificial neural network (ANN), to predict the drowsiness level of the driver.Drowsiness indicator signals are selected allowing non-intrusive measurements. The experi-mental set-up of a driver-drowsiness-monitoring system is designed on the basis of the sought-after indicator signals. These selected signals are the eye closure via pupil area measurement,gaze vector and head motion acquired by a monocular computer vision system, steering wheelangle, vehicle speed, and force applied to the steering wheel by the driver. It is believed that, byfusing these signals, driver drowsiness can be detected and drowsiness level can be predicted.For validation of this hypothesis, 30 subjects, in normal and sleep-deprived conditions, areinvolved in a standard highway simulation for 1.5 h, giving a data set of 30 pairs. For designing afeature space to be used in decision making, several metrics are derived using histograms andentropies of the signals. An FIS and an ANN are used for decision making on the drowsinesslevel. To construct the rule base of the FIS, two different methods are employed and comparedin terms of performance: first, linguistic rules from experimental studies in literature and,second, mathematically extracted rules by fuzzy subtractive clustering. The drowsiness levelsbelonging to each session are determined by the participants before and after the experiment,and videos of their faces are assessed to obtain the ground truth output for training thesystems. The FIS is able to predict correctly 98 per cent of determined drowsiness states(training set) and 89 per cent of previously unknown test set states, while the ANN has a correctclassification rate of 90 per cent for the test data. No significant difference is observed betweenthe FIS and the ANN; however, the FIS might be considered better since the rule base can beimproved on the basis of new observations.
|
|
| 15. |
- Boyraz Baykas, Pinar, 1981, et al.
(författare)
-
Robotic Surgery
- 2019
-
Ingår i: Biomechatronics. ; , s. 431-450
-
Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- In this chapter, a general overview of robotic surgery will be provided while focusing on specific developments on hyperredundant, continuum, and soft-material robotic platforms. The chapter also provides a wide and comprehensive outlook on the implications of human-machine interaction and autonomy levels in robotic surgery. To better explain the new developments in robotic surgery front, two case studies are selected reporting on the state-of-the-art applications in robotic ear surgery and hyperredundant semiautonomous robotic platforms.
|
|
| 16. |
- Boyraz Baykas, Pinar, 1981, et al.
(författare)
-
Safe Human-Robot Interaction Using Variable Stiffness, Hyper-Redundancy, and Smart Robotic Skins
- 2020
-
Ingår i: Service Robotics. - : IntechOpen. - 9781839680304
-
Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- In service robotics, safe human-robot interaction (HRI) is still an open research topic, requiring developments both in hardware and in software as well as their integration. In UMAY1 and MEDICARE-C2projects, we addressed both mechanism design and perception aspects of a framework for safe HRI. Our first focus was to design variable stiffness joints for the robotic neck and arm to enable inherent compliance to protect a human collaborator. We demonstrate the advantages of variable stiffness actuators (VSA) in compliancy, safety, and energy efficiency with applications in exoskeleton and rehabilitation robotics. The variable-stiffness robotic neck mechanism was later scaled down and adopted in the robotic endoscope featuring hyper-redundancy. The hyper-redundant structures are more controllable, having efficient actuation and better feedback. Lastly, a smart robotic skin is introduced to explain the safety support via enhancement of tactile perception. Although it is developed for a hyper-redundant endoscopic robotic platform, the artificial skin can also be integrated in service robotics to provide multimodal tactile feedback. This chapter gives an overview of systems and their integration to attain a safer HRI. We follow a holistic approach for inherent compliancy via mechanism design (i.e., variable stiffness), precise control (i.e., hyper-redundancy), and multimodal tactile perception (i.e., smart robotic-skins).
|
|
| 17. |
- Boyraz Baykas, Pinar, 1981
(författare)
-
Semantic Analysis of Driver Behavior by Data Fusion
- 2020
-
Ingår i: Vehicles, Drivers, and Safety, Edited by: Huseyin Abut, Kazuya Takeda, Gerhard Schmidt and John H.L. Hansen, (Intelligent Vehicles and Transportation, 2). - 9783110666472
-
Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- Behavioral signal processing and data-fusion have been two important components of the analytical toolbox that is used to understand driver behavior and implement advanced driver assistance systems (ADAS). The recent need for quantitative analysis of driver behavior is now driven by a new revelation that incorporating human-like behavior and control strategies in the autonomous vehicles can increase their safety and acceptability in a mixed-fleet traffic environment. In addition to that, the overall safety and efficiency of the driver-vehicle system in a conditional or partial automation (Level 2–4) can be leveraged if the perception, cognition, and action capabilities of driver are enhanced based on driving-task or traffic-scenario. Motivated by this new interest, this work attempts to define a highlevel semantic analysis framework incorporating eye-motion, road-scene, and vehicle dynamics data. The study aims to identify general trends or patterns in driver behavior, especially concerning focus of attention (FoA), based on two categories: traffic scenario and complexity. To perform semantic analysis, open database from DR(eye)VE Project is used. First, the road-scene video and vehicle dynamics data are used together to obtain a complexity measure in addition to automatic recognition of the traffic-scenario. Next, the raw eye-movement data is processed to obtain gaze distribution maps and metrics. Then, a support vector machine (SVM) is trained using gaze metrics to infer the complexity level or the traffic-scenario. To obtain better separation between two classes (i.e., low vs high complexity or urban vs highway scenarios), the SVM is trained using Bayesian optimization. The results showed that based on the gaze distribution, it is possible to distinguish between urban and highway scenarios (85% accuracy), while this distinction between complexity levels can be even stronger (98% accuracy). The framework can be used as a high-level analysis and inference tool to discover behavioral characteristics of drivers and their relation to FoA patterns.
|
|
| 18. |
- Boyraz Baykas, Pinar, 1981, et al.
(författare)
-
Signal Modelling and Hidden Markov Models for Driving Manoeuvre Recognition and Driver Fault Diagnosis in an urban road scenario
- 2007
-
Ingår i: IEEE Intelligent Vehicles Symposium, Proceedings. ; , s. 987-992
-
Konferensbidrag (refereegranskat)abstract
- Hidden Markov models (HMM) are used to identify a vehicle's manoeuvre sequence and its appropriateness for a given urban road driving situation. One of the novel aspects of this work has been the development of an efficient signal modelling approach to form a context-aware, flexible system which proved to respond well in urban road scenarios, especially in situations where the driver is likely to have an accident due to impaired performance. Another contribution has been to clarify how HMMs can be used not just to recognize vehicle manoeuvres but also to distinguish an impaired driver from a normal one in complex driving contexts. The system has worked well on simulator data and is about to be implemented in the real conditions of an urban trajectory.
|
|
| 19. |
- Boyraz Baykas, Pinar, 1981, et al.
(författare)
-
UMAY1: A Modular Humanoid Platform for Education and Rehabilitation of Children with Autism Spectrum Disorders
- 2013
-
Ingår i: 2013 9th Asian Control Conference (ASCC). - 9781467357661
-
Konferensbidrag (refereegranskat)abstract
- In this paper, a humanoid platform comprising a 6DOF robotic head will be introduced with its concept design emphasizing its motion and cognitive capabilities. The focus of the research is to obtain an effective and modular humanoid robot platform which can be used in incremental rehabilitation and education of the children with autism spectrum disorders. Therefore, the first aim is determined to form a robotic head capable of visual interaction and human-like motion of the head and eyes, keeping a simple design in mind. After the mechanical design of the head is introduced, the kinematics and dynamics of the unique 3DOF neck mechanism is detailed. The active vision system on top of the neck structure having the remaining 3DOF has currently basic capabilities such as face and/or object detection and tracking. In addition, the active vision system is designed as a modular unit and a 3D vision capability can be turned on using a Kinect depth camera depending on the task or the operating mode of the robot.
|
|
| 20. |
- Dogan, Daghan, et al.
(författare)
-
A Low-Cost Embedded Data Collection System for Traction Control Systems in Electric Vehicles
- 2019
-
Ingår i: Proceedings - 2019 IEEE International Conference on Mechatronics, ICM 2019. ; 2019, s. 513-518
-
Konferensbidrag (refereegranskat)abstract
- The transition from conventional vehicles to electric vehicles (EVs) has increased interest in research in the area of autonomy to prevent traffic accidents. Despite the relevance of the related research to the well-being of the society, commercial vehicles offered by automotive industries often do not provide the openness required for research and realistic experiments. In this paper, we propose the use of a noncommercial electric vehicle, and a novel low-cost embedded (LCE) data collection system for research and education in advanced driver-assistance systems (ADAS). This LCE data system for EV can collect vehicle-dynamics related data and environmental context via a low-cost platform. These inputs are mainly the wheel motor current indicating the torque demand, steering wheel angle, angular wheel velocity, global positioning, 3 axis acceleration, 3 axis rotation and 3 axis magnetics measurements. Using these inputs, we propose the design of a prospective traction control system that would allow for different levels of autonomy. In this work, for traction control of the EV, the maximum transmissible torque estimation method (MTTE) is used. Our experimental results demonstrate a 10% improvement in the maximum slip rate of EV.
|
|
| 21. |
- Dogan, Daghan, et al.
(författare)
-
Intelligent Traction Control in Electric Vehicles using a Novel Acoustic Approach for Online Estimation of Road-Tire Friction
- 2013
-
Ingår i: IEEE Intelligent Vehicles Symposium, Proceedings. ; , s. 1336-1343
-
Konferensbidrag (refereegranskat)abstract
- Torque control of electric motor via current gives the advantage of simplicity and fast response over the complicated torque control of an internal combustion engine which may depend on several parameters ranging from fuel valve angle to gas pedal position and several delay factors. Although traction control system (TCS) for in-wheel-motor (IWM) configuration electric vehicles (EV) has advantages, the performance of the control system, as in most traction control cases, still depends on (1)accurate estimation of road-tire friction characteristics and (2) measurement of slip ratio requiring expensive sensors for obtaining wheel and chassis velocity. The main contribution of this work is design and integration of an acoustic road-type estimation system (ARTE), which significantly increases the robustness and reduces the cost of TCS in IWM configuration EVs. Unlike complicated and expensive sensor units, the system uses a simple data collection set-up including a low-cost cardioid microphone directed to vicinity of road-tire interface. The acoustic data is then reduced to features such as linear predictive, cepstrum and power spectrum coefficients. For robust estimation, only some of these coefficients are selected based on minimum intra-class variance and maximum inter-class distance criteria to train an artificial neural network (ANN) for classification. The road types can be grouped into: Asphalt, gravel, stone and snow with a correct classification rate of 91% for the test data. The predicted road-type is used to select the correct friction characteristic curve (μ-λ) which helps calculating the appropriate torque command for the particular road-tire condition. The system has been evaluated in extensive simulations and the results show that extreme torque values are supressed stabilising the vehicle for several driving scenarios in a more energy-efficient and robust manner compared to previous systems.
|
|
| 22. |
- Dogan, Daghan, et al.
(författare)
-
Smart Traction Control Systems for Electric Vehicles Using Acoustic Road-type Estimation
- 2019
-
Ingår i: IEEE Transactions on Intelligent Vehicles. - 2379-8858. ; 4:3, s. 486-496
-
Tidskriftsartikel (refereegranskat)abstract
- The application of traction control systems (TCS) for electric vehicles (EV) has great potential due to easy implementation of torque control with direct-drive motors. However, the control system usually requires road-tire friction and slip-ratio values, which must be estimated. While it is not possible to obtain the first one directly, the estimation of latter value requires accurate measurements of chassis and wheel velocity. In addition, existing TCS structures are often designed without considering the robustness and energy efficiency of torque control. In this paper, both problems are addressed with a smart TCS design having an integrated acoustic road-type estimation (ARTE) unit. This unit enables the road-type recognition and this information is used to retrieve the correct look-up table between friction coefficient and slip-ratio. The estimation of the friction coefficient helps the system to update the necessary input torque. The ARTE unit utilizes machine learning, mapping the acoustic feature inputs to road-type as output. In this paper, three existing TCS for EVs are examined with and without the integrated ARTE unit. The results show significant performance improvement with ARTE, reducing the slip ratio by 75% while saving energy via reduction of applied torque and increasing the robustness of the TCS.
|
|
| 23. |
- Ercan, Hasan, et al.
(författare)
-
Design of a Modular Mobile Multi Robot System: ULGEN (Universal-Generative Robot)
- 2016
-
Ingår i: Proceedings of 2016 Asia-Pacific Conference on Intelligent Robot Systems, ACIRS 2016. - 9781509013623 ; , s. 8-15
-
Konferensbidrag (refereegranskat)abstract
- This paper presents a chain type, homogenous, mobile and modular multi-robot system (ULGEN) with self-assembly, self-reconfigurability, localization and high mobility capabilities. The main goal of the work is to have high maneuverable modules which can travel autonomously to explore areas individually and change their configuration when encountering obstacles. Once the optimal path is found by any of the individual modules, the whole system can re-assemble and follow that path. Five degrees of freedom and six active docking faces makes a single module adapt to different tasks, avoid obstacles, and reconfigure as a structure. A single module can achieve locomotion in crawler and differential drive modes on its wheels. The rotating central joint brings up different capabilities, such as - recovering itself when the module falls on its side, changing the locomotion type without reconfiguring the whole structure while switching from the skid-steering mode to 4-wheel steering mode or insect-like four-legged robot mode to mammal-like four-legged robot mode. In this paper, the hardware and software architectures are discussed. Locomotion types and possible configurations are modelled in a simulation environment. Finally, single module locomotion types are implemented on the prototype.
|
|
| 24. |
- Flannagan, Carol A., et al.
(författare)
-
Analysis of SHRP2 Data to Understand Normal and Abnormal Driving Behavior in Work Zones
- 2019
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- This research project used the Second Strategic Highway Research Program (SHRP2) Naturalistic Driving Study(NDS) to improve highway safety by using statistical descriptions of normal driving behavior to identify abnormal driving behaviors in work zones. SHRP2 data used in these analyses included 50 safety-critical events (SCEs) from work zones and 444 baseline events selected on a matched case-control design. Principal components analysis (PCA) was used to summarize kinematic data into “normal” and “abnormal”driving. Each second of driving is described by one point in three-dimensional principal component (PC) space;an ellipse containing the bulk of baseline points is considered “normal” driving. Driving segments without-of-ellipse points have a higher probability of being an SCE. Matched case-control analysis indicates that thespecific individual and traffic flow made approximately equal contributions to predicting out-of-ellipse driving. Structural Topics Modeling (STM) was used to analyze complex categorical data obtained from annotated videos.The STM method finds “words” representing categorical data variables that occur together in many events and describes these associations as “topics.” STM then associates topics with either baselines or SCEs. The STM produced 10 topics: 3 associated with SCEs, 5 associated with baselines, and 2 that were neutral. Distractionoccurs in both baselines and SCEs. Both approaches identify the role of individual drivers in producing situations where SCEs might arise. A countermeasure could use the PC calculation to indicate impending issues or specific drivers who may havehigher crash risk, but not to employ significant interventions such as automatically braking a vehicle without-of-ellipse driving patterns. STM results suggest communication to drivers or placing compliant vehicles in thetraffic stream would be effective. Finally, driver distraction in work zones should be discouraged.
|
|
| 25. |
- Kleinschmidt, Tristan, et al.
(författare)
-
Assessment of Speech Dialog Systems using Multi-modal Cognitive Load Analysis and Driving Performance Metrics
- 2009
-
Ingår i: 2009 IEEE International Conference on Vehicular Electronics and Safety (ICVES). - 9781424454419 ; , s. 162-167
-
Konferensbidrag (refereegranskat)abstract
- In this paper, cognitive load analysis via acoustic-and CAN-Bus-based driver performance metrics is employed to assess two different commercial speech dialog systems (SDS) during in-vehicle use. Several metrics are proposed to measure increases in stress, distraction and cognitive load and we compare these measures with statistical analysis of the speech recognition component of each SDS. It is found that care must be taken when designing an SDS as it may increase cognitive load which can be observed through increased speech response delay (SRD), changes in speech production due to negative emotion towards the SDS, and decreased driving performance on lateral control tasks. From this study, guidelines are presented for designing systems which are to be used in vehicular environments.
|
|
| 26. |
- Luces, Mario, et al.
(författare)
-
An Emulator-Based Prediction of Dynamic Stiffness for Redundant Parallel Kinematic Mechanisms
- 2016
-
Ingår i: Journal of Mechanisms and Robotics. - : ASME International. - 1942-4310 .- 1942-4302. ; 8:2
-
Tidskriftsartikel (refereegranskat)abstract
- The accuracy of a parallel kinematic mechanism (PKM) is directly related to its dynamic stiffness, which in turn is configuration dependent. For PKMs with kinematic redundancy, configurations with higher stiffness can be chosen during motion-trajectory planning for optimal performance. Herein, dynamic stiffness refers to the deformation of the mechanism structure, subject to dynamic loads of changing frequency. The stiffness-optimization problem has two computational constraints: (i) calculation of the dynamic stiffness of any considered PKM configuration, at a given task-space location, and (ii) searching for the PKM configuration with the highest stiffness at this location. Due to the lack of available analytical models, herein, the former subproblem is addressed via a novel effective emulator to provide a computationally efficient approximation of the high-dimensional dynamic-stiffness function suitable for optimization. The proposed method for emulator development identifies the mechanism's structural modes in order to breakdown the high-dimensional stiffness function into multiple functions of lower dimension. Despite their computational efficiency, however, emulators approximating high-dimensional functions are often difficult to develop and implement due to the large amount of data required to train the emulator. Reducing the dimensionality of the approximation function would, thus, result in a smaller training data set. In turn, the smaller training data set can be obtained accurately via finite-element analysis (FEA). Moving least-squares (MLS) approximation is proposed herein to compute the low-dimensional functions for stiffness approximation. Via extensive simulations, some of which are described herein, it is demonstrated that the proposed emulator can predict the dynamic stiffness of a PKM at any given configuration with high accuracy and low computational expense, making it quite suitable for most high-precision applications. For example, our results show that the proposed methodology can choose configurations along given trajectories within a few percentage points of the optimal ones.
|
|
| 27. |
- Pereira, Mike, 1992, et al.
(författare)
-
Parameter and density estimation from real-world traffic data: A kinetic compartmental approach
- 2022
-
Ingår i: Transportation Research Part B: Methodological. - : Elsevier BV. - 0191-2615. ; 155, s. 210-239
-
Tidskriftsartikel (refereegranskat)abstract
- The main motivation of this work is to assess the validity of a LWR traffic flow model to model measurements obtained from trajectory data, and propose extensions of this model to improve it. A formulation for a discrete dynamical system is proposed aiming at reproducing the evolution in time of the density of vehicles along a road, as observed in the measurements. This system is formulated as a chemical reaction network where road cells are interpreted as compartments, the transfer of vehicles from one cell to the other is seen as a chemical reaction between adjacent compartment and the density of vehicles is seen as a concentration of reactant. Several degrees of flexibility on the parameters of this system, which basically consist of the reaction rates between the compartments, can be considered: a constant value or a function depending on time and/or space. Density measurements coming from trajectory data are then interpreted as observations of the states of this system at consecutive times. Optimal reaction rates for the system are then obtained by minimizing the discrepancy between the output of the system and the state measurements. This approach was tested both on simulated and real data, proved successful in recreating the complexity of traffic flows despite the assumptions on the flux-density relation.
|
|
| 28. |
- Popovic, Marko B., et al.
(författare)
-
Practice Problems
- 2019
-
Ingår i: Biomechatronics. ; , s. 567-604
-
Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- Selected practice problems in the format of numerical problems, concept questions, and case studies are presented in this chapter. Each problem is labeled with an estimated level of difficulty and list of most relevant chapters. Solutions and hints for about half of these problems are provided in the following chapter.
|
|
| 29. |
- Sathyanarayana, Amardeep, et al.
(författare)
-
Driver adaptive and context aware active safety systems using CAN-bus signals
- 2010
-
Ingår i: IEEE Intelligent Vehicles Symposium, Proceedings. ; xx, s. 1236-1241
-
Konferensbidrag (refereegranskat)abstract
- Increasing stress levels in drivers, along with their ability to multi task with infotainment systems cause the drivers to deviate their attention from the primary task of driving. With the rapid advancements in technology, along with the development of infotainment systems, much emphasis is being given to occupant safety. Modern vehicles are equipped with many sensors and ECUs (Embedded Control Units) and CAN-bus (Controller Area Network) plays a significant role in handling the entire communication between the sensors, ECUs and actuators. Most of the mechanical links are replaced by intelligent processing units (ECU) which take in signals from the sensors and provide measurements for proper functioning of engine and vehicle functionalities along with several active safety systems such as ABS (Anti-lock Brake System) and ESP (Electronic Stability program). Current active safety systems utilize the vehicle dynamics (using signals on CAN-bus) but are unaware of context and driver status, and do not adapt to the changing mental and physical conditions of the driver. The traditional engine and active safety systems use a very small time window (t<;2sec) of the CAN-bus to operate. On the contrary, the implementation of driver adaptive and context aware systems require longer time windows and different methods for analysis. The long-term history and trends in the CAN-bus signals contain important information on driving patterns and driver characteristics. In this paper, a summary of systems that can be built on this type of analysis is presented. The CAN-bus signals are acquired and analyzed to recognize driving sub-tasks, maneuvers and routes. Driver inattention is assessed and an overall system which acquires, analyses and warns the driver in real-time while the driver is driving the car is presented showing that an optimal human-machine cooperative system can be designed to achieve improved overall safety.
|
|
| 30. |
- Sathyanarayana, Amardeep, et al.
(författare)
-
Driver behavior analysis and route recognition by Hidden Markov Models
- 2008
-
Ingår i: 2008 IEEE International Conference on Vehicular Electronics and Safety. - 9781424423590
-
Konferensbidrag (refereegranskat)abstract
- In this investigation, driver behavior signals are modeled using Hidden Markov Models (HMM) in two different and complementary approaches. The first approach considers isolated maneuver recognition with model concatenation to construct a generic route (bottom-to-top), whereas the second approach models the entire route as a dasiaphrasepsila and refines the HMM to discover maneuvers and parses the route using finer discovered maneuvers (top-to-bottom). By applying these two approaches, a hierarchical framework to model driver behavior signals is proposed. It is believed that using the proposed approach, driver identification and distraction detection problems can be addressed in a more systematic and mathematically sound manner. We believe that this framework and the initial results will encourage more investigations into driver behavior signal analysis and related safety systems employing a partitioned sub-module strategy.
|
|
| 31. |
- Sathyanarayana, Amardeep, et al.
(författare)
-
Information Fusion for Context and Driver Aware Active Vehicle Safety Systems
- 2011
-
Ingår i: Information Fusion. - : Elsevier BV. - 1566-2535. ; 12:4, s. 293-303
-
Tidskriftsartikel (refereegranskat)abstract
- Although there is currently significant development in active vehicle safety (AVS) systems, the number of accidents, injury severity levels and fatalities has not reduced. In fact, human error, low performance, drowsiness and distraction may account for a majority in all the accident causation. Active safety systems are unaware of the context and driver status, so these systems cannot improve these figures. Therefore, this study proposes a ‘context and driver aware’ (CDA) AVS system structure as a first step in realizing robust, human-centric and intelligent active safety systems. This work develops, evaluates and combines three sub-modules all employing a Gaussian Mixture Model (GMM)/Universal Background Model (UBM) and likelihood maximization learning scheme: biometric driver identification, maneuver recognition, and distraction detection. The resultant combined system contributes in three areas: (1) robust identification: a speaker recognition system is developed in an audio modality to identify the driver in-vehicle conditions requiring robust operation; (2) narrow the available information space for fusion: maneuver recognition system uses estimated driver identification to prune the selection of models and further restrict search space in a novel distraction detection system; (3) response time and performance: the system quickly produces a prediction of driver’s distracted behaviour for possible use in accident prevention/avoidance. Overall system performance of the combined system is evaluated on the UTDrive Corpus, confirming the suitability of the proposed system for critical imminent accident cases with narrow time windows.
|
|
| 32. |
- Sert, Emre, et al.
(författare)
-
Enhancement of Vehicle Handling Based on Rear Suspension Geometry Using Taguchi Method
- 2016
-
Ingår i: SAE International Journal of Commercial Vehicles. - : SAE International. - 1946-3928 .- 1946-391X. ; 9:1, s. 1-13
-
Tidskriftsartikel (refereegranskat)abstract
- Studies have shown that the number of road accidents caused by rollover both in Europe and in Turkey is increasing [1]. Therefore, rollover related accidents became the new target of the studies in the field of vehicle dynamics research aiming for both active and passive safety systems. This paper presents a method for optimizing the rear suspension geometry using design of experiment and multibody simulation in order to reduce the risk of rollover. One of the major differences of this study from previous work is that it includes statistical Taguchi method in order to increase the safety margin. Other difference of this study from literature is that it includes all design tools such as model validation, optimization and full vehicle handling and ride comfort tests. Rollover angle of the vehicle was selected as the cost function in the optimization algorithm that also contains roll stiffness and height of the roll center. In order to form the cost function, five different geometrical factors have been selected as design variables. The ultimate aim is to minimize the cost function by increasing the roll center height and suspension roll stiffness. To run the optimization routine, a rigid rear suspension mechanism used on the 7 m bus has been modeled using Adams/Car software program. Opposite wheel travel analysis has been performed as an optimization test method in order to simulate the vehicle passing over the bump. Then, in order to reach the minimum value of the cost function, statistical Taguchi method was used to perform design of experiments (DOE). In total, 27 experiments have been performed according to the selected design variables. Therefore, in each different experiment, the roll center height and the roll stiffness were measured. Then, the cost function was calculated and recorded to compare with the future iterations. The attachment points giving minimum cost function value are expected to be the optimal coordinates for installing the suspension mechanism.
|
|
| 33. |
- Sert, Emre, et al.
(författare)
-
Optimization of suspension system and sensitivity analysis for improvement of stability in a midsize heavy vehicle
- 2017
-
Ingår i: Engineering Science and Technology (JESTECH). - : Elsevier BV. - 2215-0986. ; 20:3, s. 997-1012
-
Tidskriftsartikel (refereegranskat)abstract
- This paper presents a method for systematic investigations on static and dynamic roll behavior and improvement to the stability dynamics based on increasing roll stiffness of the suspension. One of the major differences of this study from previous work is that it includes parametric sensitivity analysis in order to increase the safety margin from the roll angle threshold using the static and dynamic tests and it compares the results within themselves. As the physical tilt table test cannot be continued until vehicle rollover actually occurs, this test was performed in a simulation with verified vehicle model using Adams/Car. Three different front anti-roll bars and two different front leaf springs were used during the tests in order to perform parametric sensitivity analysis and examine the effect of components on the stability performance. In summary, within the scope of this work, unlike the previous studies, experiments involving physical tests (i.e. tilt table, fishhook and cornering) and numerical calculations are included. In addition, verification of the virtual model, parametric sensitivity analysis and the comparison of the virtual test and the physical test is performed. Because of the vigorous verification, sensitivity analysis and validation process, the results can be more reliable compared to previous studies.
|
|
| 34. |
- Takeda, Kazuya, et al.
(författare)
-
An International Large-Scale Vehicle Corpora for Research on Driver Behavior on the Road
- 2011
-
Ingår i: IEEE Transactions on Intelligent Transportation Systems. - 1524-9050 .- 1558-0016. ; 12:4, s. 1609-1623
-
Tidskriftsartikel (refereegranskat)abstract
- This paper considers a comprehensive and collaborative project to collect large amounts of driving data on the road for use in a wide range of areas of vehicle-related research centered on driving behavior. Unlike previous data collection efforts, the corpora collected here contain both human and vehicle sensor data, together with rich and continuous transcriptions. While most efforts on in-vehicle research are generally focused within individual countries, this effort links a collaborative team from three diverse regions (i.e., Asia, American, and Europe). Details relating to the data collection paradigm, such as sensors, driver information, routes, and transcription protocols, are discussed, and a preliminary analysis of the data across the three data collection sites from the U.S. (Dallas), Japan (Nagoya), and Turkey (Istanbul) is provided. The usability of the corpora has been experimentally verified with a Cohen's kappa coefficient of 0.74 for transcription reliability, as well as being successfully exploited for several in-vehicle applications. Most importantly, the corpora are publicly available for research use and represent one of the first multination efforts to share resources and understand driver characteristics. Future work on distributing the corpora to the wider research community is also discussed.
|
|
| 35. |
- Tappe, Svenja, et al.
(författare)
-
Design, Production and Integration of a Shape Sensing Robotic Sleeve for a Hyper-Redundant, Binary Actuated Robot
- 2018
-
Ingår i: 2018 IEEE/ASME INTERNATIONAL CONFERENCE ON ADVANCED INTELLIGENT MECHATRONICS (AIM). - 2159-6255. - 9781538618547 - 9781538618547 ; 2018-July, s. 298-303
-
Konferensbidrag (refereegranskat)abstract
- Endoscopes have become a common tool for a variety of examination tasks in areas that are difficult to access. Robotic endoscope systems aim to combine two main requirements for a fast, precise and safe operation: Good path following capabilities as well as high resistance against manipulation forces. In this context, a hyper-redundant shaft concept based on unique binary, electromagnetic tilting actuators was proposed earlier. To keep the actuator as simple as possible, no sensors were integrated. In order to close the control loop and capture the current configuration of the shaft in combination with establishing a safe interaction interface between the electromagnetic manipulator and its environment, this paper addresses preliminary design issues and first results for a sensor equipped silicon sheath for the robotic system.
|
|
| 36. |
- Yigit, Cihat Bora, et al.
(författare)
-
Design and Modelling of a Cable-Driven Parallel-Series Hybrid Variable Stiffness Joint Mechanism for Robotics
- 2017
-
Ingår i: Mechanical Sciences. - : Copernicus GmbH. - 2191-916X. ; 8, s. 65-77
-
Tidskriftsartikel (refereegranskat)abstract
- The robotics, particularly the humanoid research field, needs new mechanisms to meet the criteria enforced by compliance, workspace requirements, motion profile characteristics and variable stiffness using lightweight but robust designs. The mechanism proposed herein is a solution to this problem by a parallel-series hybrid mechanism. The parallel term comes from two cable-driven plates supported by a compression spring in between. Furthermore, there is a two-part concentric shaft, passing through both plates connected by a universal joint. Because of the kinematic constraints of the universal joint, the mechanism can be considered as a serial chain. The mechanism has 4 degrees of freedom (DOF) which are pitch, roll, yaw motions and translational movement in z axis for stiffness adjustment. The kinematic model is obtained to define the workspace. The helical spring is analysed by using Castigliano's Theorem and the behaviour of bending and compression characteristics are presented which are validated by using finite element analysis (FEA). Hence, the dynamic model of the mechanism is derived depending on the spring reaction forces and moments. The motion experiments are performed to validate both kinematic and dynamic models. As a result, the proposed mechanism has a potential use in robotics especially in humanoid robot joints, considering the requirements of this robotic field.
|
|
| 37. |
- Yigit, Cihat Bora, et al.
(författare)
-
External Force/Torque Estimation With Only Position Sensors for Antagonistic VSAs
- 2021
-
Ingår i: IEEE Transactions on Robotics. - 1552-3098 .- 1941-0468. ; 37:2, s. 675-682
-
Tidskriftsartikel (refereegranskat)abstract
- Recent use scenarios involving human-robot collaboration have revealed that the robots require elastic joints to safely interact with humans. It is also critical to know applied force/torque (f/t) during the interaction for control and motion planning purposes. In this article, we estimate the external f/t values without using any sensors other than low-cost encoders by exploiting the inherent elastic properties of the joint. For estimation, the following two different approaches are used: model based and model free. In the model-based approach, an extended Kalman filter (EKF) and an external force observer (EFOB) are used considering the dynamical behavior of the system to estimate the interaction force. In the model-free approach, the artificial neural network (ANN) utilizes the data gathered from mechanical systems. In comparative analysis, we have, therefore, considered three different estimation methods, two of which are model based and the remaining one is model free (i.e., data driven). Implementing these estimation algorithms experimentally on a variable stiffness joint, we performed an extensive evaluation of their performances. All methods show similar level of performance in terms of the root-mean-square (RMS) error with 0.0847, 0.0841, and 0.1082 N for the EKF, EFOB, and ANN, respectively. Model-based methods do not require continuous data stream through the experimental set up. On the other hand, the ANN does not need an explicit model of the system; therefore, it may become preferable when the detailed model derivation is not possible.
|
|
| 38. |
- Yigit, Cihat Bora, et al.
(författare)
-
Low-cost variable stiffness joint design using translational variable radius pulleys
- 2018
-
Ingår i: Mechanism and Machine Theory. - : Elsevier BV. - 0094-114X. ; 130, s. 203-219
-
Tidskriftsartikel (refereegranskat)abstract
- Robot joints are expected to be safe, compliant, compact, simple and low-cost. Gravity compensation, zero backlash, energy efficiency and stiffness adjustability are some desired features in the robotic joints. The variable radius pulleys (VRPs) provide a simple, compact and low-cost solution to the stiffness adjustment problem. VRP mechanisms maintain a preconfigured nonlinear force-elongation curve utilizing off-the-shelf torsional spring and pulley profile. In this paper, three synthesis algorithms are presented for VRP mechanisms to obtain desired force-elongation curve. In addition, a feasibility condition is proposed to determine the torsional spring coefficient. Using the synthesis methods and the feasibility condition, a variable stiffness mechanism is designed and manufactured which uses two VRPs in an antagonistic cable driven structure. Afterwards, the outputs of three synthesis methods are compared to force-elongation characteristics in the tensile testing experiment. A custom testbed is manufactured to measure the pulley rotation, cable elongation and tensile force at the same time. Using the experiment as the baseline, the best algorithm achieved to reproduce the desired curve with a root-mean-square (RMS) error of 13.3%. Furthermore, VRP-VSJ is implemented with a linear controller to reveal the performance of the mechanism in terms of position accuracy and stiffness adjustability.
|
|
| 39. |
- Özcan, Banş, et al.
(författare)
-
A MonoSLAM Approach to Lane Departure Warning System
- 2014
-
Ingår i: 2014 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM 2014). - 9781479957378 ; , s. 640-645
-
Konferensbidrag (refereegranskat)abstract
- Lane Departure Warning (LDW) systems are one of the widely researched topics under Advanced Driver Assistance Systems (ADAS), because they are seen as the most viable way to prevent the traffic accidents caused by involuntary lane departures from happening. Various methods and algorithms used for lane tracking to be used in LDW in the literature; however, most of them only track the lanes or the position of the vehicle inside the lane. This article introduces MonoSLAM based method for LDW design, assuming that the camera is moving in a previously unknown scene. While applying this method, a constant lateral velocity model for the vehicle is used, which assumes that the vehicle is exposed to undetermined Gaussian lateral accelerations. As the first output, the localization of the vehicle on the road is achieved. Moreover, the method is applied with a low cost webcam attached on a vehicle. Five control points for each lane is used to track the lanes and these control points are modelled as if they have a constant position. Detection is made with steerable filters exploiting the state covariance from EKF to make detection more robust. In addition to this, off-line experimental results are given for 200 frames. Results of lane slope on image plane compared with ground truth marked manually for performance benchmarking and localization estimation of a scenario similar to loop closure test is given.
|
|
