| 1. |
- Abdul Khaliq, Ali, 1987-, et al.
(författare)
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Point-to-point safe navigation of a mobile robot using stigmergy and RFID technology
- 2016
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Ingår i: 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). - : Institute of Electrical and Electronics Engineers (IEEE). - 9781509037629 ; , s. 1497-1504
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Konferensbidrag (refereegranskat)abstract
- Reliable autonomous navigation is still a challenging problem for robots with simple and inexpensive hardware. A key difficulty is the need to maintain an internal map of the environment and an accurate estimate of the robot’s position in this map. Recently, a stigmergic approach has been proposed in which a navigation map is stored into the environment, on a grid of RFID tags, and robots use it to optimally reach predefined goal points without the need for internal maps. While effective,this approach is limited to a predefined set of goal points. In this paper, we extend this approach to enable robots to travel to any point on the RFID floor, even if it was not previously identified as a goal location, as well as to keep a safe distance from any given critical location. Our approach produces safe, repeatable and quasi-optimal trajectories without the use of internal maps, self localization, or path planning. We report experiments run in a real apartment equipped with an RFID floor, in which a service robot either reaches or avoids a user who wears slippers equipped with an RFID tag reader.
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| 2. |
- Bagge Carlson, Fredrik, et al.
(författare)
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Particle Filter Framework for 6D Seam Tracking Under Large External Forces Using 2D Laser Sensors
- 2016
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Ingår i: 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems. - 9781509037629 ; , s. 3728-3734
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Konferensbidrag (refereegranskat)abstract
- We provide a framework for 6 DOF pose estimation in seam-tracking applications using particle filtering. The particle filter algorithm developed incorporates measurements from both a 2 DOF laser seam tracker and the robot forward kinematics under an assumed external force. Special attention is paid to modeling of disturbances in the respective measurements, and methods are developed to assist the selection of sensor configurations for optimal estimation performance. The developed estimation algorithm and simulation environment are provided as an open-source, extendable package, written with an intended balance between readability and performance.
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| 3. |
- Caccamo, Sergio, et al.
(författare)
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Active Exploration Using Gaussian Random Fields and Gaussian Process Implicit Surfaces
- 2016
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Ingår i: IEEE International Conference on Intelligent Robots and Systems. - : Institute of Electrical and Electronics Engineers (IEEE). - 2153-0858. - 9781509037629 ; , s. 582-589
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Konferensbidrag (refereegranskat)abstract
- In this work we study the problem of exploring surfaces and building compact 3D representations of the environment surrounding a robot through active perception. We propose an online probabilistic framework that merges visual and tactile measurements using Gaussian Random Field and Gaussian Process Implicit Surfaces. The system investigates incomplete point clouds in order to find a small set of regions of interest which are then physically explored with a robotic arm equipped with tactile sensors. We show experimental results obtained using a PrimeSense camera, a Kinova Jaco2 robotic arm and Optoforce sensors on different scenarios. We then demostrate how to use the online framework for object detection and terrain classification.
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| 4. |
- Evestedt, Niclas, et al.
(författare)
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Motion planning for a reversing general 2-trailer configuration using Closed-Loop RRT
- 2016
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Ingår i: 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). - : Institute of Electrical and Electronics Engineers (IEEE). - 9781509037629 - 9781509037612 - 9781509037636 ; , s. 3690-3697
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Konferensbidrag (refereegranskat)abstract
- Reversing with a dolly steered trailer configura- tion is a hard task for any driver without extensive training. In this work we present a motion planning and control framework that can be used to automatically plan and execute complicated manoeuvres. The unstable dynamics of the reversing general 2- trailer configuration with off-axle hitching is first stabilised by an LQ-controller and then a pure pursuit path tracker is used on a higher level giving a cascaded controller that can track piecewise linear reference paths. This controller together with a kinematic model of the trailer configuration is then used for forward simulations within a Closed-Loop Rapidly Exploring Random Tree framework to generate motion plans that are not only kinematically feasible but also include the limitations of the controller’s tracking performance when reversing. The approach is evaluated over a series of Monte Carlo simulations on three different scenarios and impressive success rates are achieved. Finally the approach is successfully tested on a small scale test platform where the motion plan is calculated and then sent to the platform for execution.
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| 5. |
- Ghadirzadeh, Ali, et al.
(författare)
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A sensorimotor reinforcement learning framework for physical human-robot interaction
- 2016
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Ingår i: IEEE International Conference on Intelligent Robots and Systems. - : IEEE. - 9781509037629 ; , s. 2682-2688
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Konferensbidrag (refereegranskat)abstract
- Modeling of physical human-robot collaborations is generally a challenging problem due to the unpredictive nature of human behavior. To address this issue, we present a data-efficient reinforcement learning framework which enables a robot to learn how to collaborate with a human partner. The robot learns the task from its own sensorimotor experiences in an unsupervised manner. The uncertainty in the interaction is modeled using Gaussian processes (GP) to implement a forward model and an actionvalue function. Optimal action selection given the uncertain GP model is ensured by Bayesian optimization. We apply the framework to a scenario in which a human and a PR2 robot jointly control the ball position on a plank based on vision and force/torque data. Our experimental results show the suitability of the proposed method in terms of fast and data-efficient model learning, optimal action selection under uncertainty and equal role sharing between the partners.
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| 6. |
- Hernandez Bennetts, Victor, 1980-, et al.
(författare)
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Towards occupational health improvement in foundries through dense dust and pollution monitoring using a complementary approach with mobile and stationary sensing nodes
- 2016
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Ingår i: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). - : Institute of Electrical and Electronics Engineers (IEEE). - 9781509037629 ; , s. 131-136
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Konferensbidrag (refereegranskat)abstract
- In industrial environments, such as metallurgic facilities, human operators are exposed to harsh conditions where ambient air is often polluted with quartz, dust, lead debris and toxic fumes. Constant exposure to respirable particles can cause irreversible health damages and thus it is of high interest for occupational health experts to monitor the air quality on a regular basis. However, current monitoring procedures are carried out sparsely, with data collected in single day campaigns limited to few measurement locations. In this paper we explore the use and present first experimental results of a novel heterogeneous approach that uses a mobile robot and a network of low cost sensing nodes. The proposed system aims to address the spatial and temporal limitations of current monitoring techniques. The mobile robot, along with standard localization and mapping algorithms, allows to produce short term, spatially dense representations of the environment where dust, gas, ambient temperature and airflow information can be modelled. The sensing nodes on the other hand, can collect temporally dense (and usually spatially sparse) information during long periods of time, allowing in this way to register for example, daily variations in the pollution levels. Using data collected with the proposed system in an steel foundry, we show that a heterogeneous approach provides dense spatio-temporal information that can be used to improve the working conditions in industrial facilities.
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| 7. |
- Jung, Hojung, et al.
(författare)
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Multi-modal panoramic 3D outdoor datasets for place categorization
- 2016
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Ingår i: 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). - : IEEE Press. - 9781509037629 ; , s. 4545-4550
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Konferensbidrag (refereegranskat)abstract
- We present two multi-modal panoramic 3D outdoor (MPO) datasets for semantic place categorization with six categories: forest, coast, residential area, urban area and indoor/outdoor parking lot. The first dataset consists of 650 static panoramic scans of dense (9,000,000 points) 3D color and reflectance point clouds obtained using a FARO laser scanner with synchronized color images. The second dataset consists of 34,200 real-time panoramic scans of sparse (70,000 points) 3D reflectance point clouds obtained using a Velodyne laser scanner while driving a car. The datasets were obtained in the city of Fukuoka, Japan and are publicly available in [1], [2]. In addition, we compare several approaches for semantic place categorization with best results of 96.42% (dense) and 89.67% (sparse).
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| 8. |
- Karaoǧuz, Hakan, et al.
(författare)
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Merging appearance-based spatial knowledge in multirobot systems
- 2016
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Ingår i: IEEE International Conference on Intelligent Robots and Systems. - : IEEE. - 9781509037629 ; , s. 5107-5112
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Konferensbidrag (refereegranskat)abstract
- This paper considers the merging of appearancebased spatial knowledge among robots having compatible visual sensing. Each robot is assumed to retain its knowledge in its individual long-term spatial memory where i) the place knowledge and their spatial relations are retained in an organized manner in place and map memories respectively; and ii) a 'place' refers to a spatial region as designated by a collection of associated appearances. In the proposed approach, each robot communicates with another robot, receives its memory and then merges the received knowledge with its own. The novelty of the merging process is that it is done in two stages: merging of place knowledge followed by the merging of map knowledge. As each robot's place memory is processed as a whole or in portions, the merging process scales easily with respect to the amount and overlap of the appearance data. Furthermore, the merging can be done in decentralized manner. Our experimental results with a team of three robots demonstrate that the resulting merged knowledge enables the robots to reason about learned places.
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| 9. |
- Mosberger, Rafael, 1980-, et al.
(författare)
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Inferring human body posture information from reflective patterns of protective work garments
- 2016
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Ingår i: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). - : Institute of Electrical and Electronics Engineers (IEEE). - 9781509037629 ; , s. 4131-4136
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Konferensbidrag (refereegranskat)abstract
- We address the problem of extracting human body posture labels, upper body orientation and the spatial location of individual body parts from near-infrared (NIR) images depicting patterns of retro-reflective markers. The analyzed patterns originate from the observation of humans equipped with protective high-visibility garments that represent common safety equipment in the industrial sector. Exploiting the shape of the observed reflectors we adopt shape matching based on the chamfer distance and infer one of seven discrete body posture labels as well as the approximate upper body orientation with respect to the camera. We then proceed to analyze the NIR images on a pixel scale and estimate a figure-ground segmentation together with human body part labels using classification of densely extracted local image patches. Our results indicate a body posture classification accuracy of 80% and figure-ground segmentations with 87% accuracy.
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| 10. |
- Ótão Pereira, Pedro Miguel, et al.
(författare)
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Decoupled Design of Controllers for Aerial Manipulation with Quadrotors
- 2016
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Ingår i: 2016 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS 2016). - 9781509037629 ; , s. 4849-4855
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Konferensbidrag (refereegranskat)abstract
- In this paper, we model an aerial vehicle, specifically a quadrotor, and a load attached to each other by a rigid link. We assume a torque input at the joint between the aerial vehicle and the rigid link is available. After modeling, we decouple the system dynamics in two separate subsystems, one concerning the position of the center of mass, which we control independently from the chosen torque input; and a second subsystem, concerning the attitude of the rigid link, which we control by appropriately designing a torque control law. Differential flatness is used to show that controlling these two separate systems is equivalent to controlling the complete system. We design control laws for the quadrotor thrust, the quadrotor angular velocity and the torque input, and provide convergence proofs that guarantee that the quadrotor follows asymptotically a desired position trajectory while the manipulator follows a desired orientation. Simulation and experimental works are presented which validate the proposed algorithms.
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