| 1. |
- Andreasson, Henrik, 1977-, et al.
(författare)
-
Gold-fish SLAM : An application of SLAM to localize AGVs
- 2014
-
Ingår i: Field and Service Robotics. - Heidelberg : Springer. - 9783642406850 - 9783642406867 ; , s. 585-598
-
Konferensbidrag (refereegranskat)abstract
- The main focus of this paper is to present a case study of a SLAM solution for Automated Guided Vehicles (AGVs) operating in real-world industrial environments. The studied solution, called Gold-fish SLAM, was implemented to provide localization estimates in dynamic industrial environments, where there are static landmarks that are only rarely perceived by the AGVs. The main idea of Gold-fish SLAM is to consider the goods that enter and leave the environment as temporary landmarks that can be used in combination with the rarely seen static landmarks to compute online estimates of AGV poses. The solution is tested and verified in a factory of paper using an eight ton diesel-truck retrofitted with an AGV control system running at speeds up to 3m/s. The paper includes also a general discussion on how SLAM can be used in industrial applications with AGVs. © Springer-Verlag Berlin Heidelberg 2014.
|
|
| 2. |
- Bouguerra, Abdelbaki, 1974-, et al.
(författare)
-
An autonomous robotic system for load transportation
- 2009
-
Ingår i: 2009 IEEE Conference on Emerging Technologies & Factory Automation (EFTA 2009). - New York : IEEE conference proceedings. - 9781424427277 - 9781424427284 ; , s. 1563-1566
-
Konferensbidrag (refereegranskat)abstract
- This paper presents an overview of an autonomous robotic material handling system. The goal of the system is to extend the functionalities of traditional AGVs to operate in highly dynamic environments. Traditionally, the reliable functioning of AGVs relies on the availability of adequate infrastructure to support navigation. In the target environments of our system, such infrastructure is difficult to setup in an efficient way. Additionally, the location of objects to handle are unknown, which requires that the system be able to detect and track object positions at runtime. Another requirement of the system is to be able to generate trajectories dynamically, which is uncommon in industrial AGV systems.
|
|
| 3. |
- Englund, Cristofer, 1977-, et al.
(författare)
-
AI Perspectives in Smart Cities and Communities to Enable Road Vehicle Automation and Smart Traffic Control
- 2021
-
Ingår i: Smart Cities. - Basel : MDPI. - 2624-6511. ; 4:2, s. 783-802
-
Tidskriftsartikel (refereegranskat)abstract
- Smart Cities and Communities (SCC) constitute a new paradigm in urban development. SCC ideates on a data-centered society aiming at improving efficiency by automating and optimizing activities and utilities. Information and communication technology along with internet of things enables data collection and with the help of artificial intelligence (AI) situation awareness can be obtained to feed the SCC actors with enriched knowledge. This paper describes AI perspectives in SCC and gives an overview of AI-based technologies used in traffic to enable road vehicle automation and smart traffic control. Perception, Smart Traffic Control and Driver Modelling are described along with open research challenges and standardization to help introduce advanced driver assistance systems and automated vehicle functionality in traffic. To fully realize the potential of SCC, to create a holistic view on a city level, the availability of data from different stakeholders is need. Further, though AI technologies provide accurate predictions and classifications there is an ambiguity regarding the correctness of their outputs. This can make it difficult for the human operator to trust the system. Today there are no methods that can be used to match function requirements with the level of detail in data annotation in order to train an accurate model. Another challenge related to trust is explainability, while the models have difficulties explaining how they come to a certain conclusions it is difficult for humans to trust it. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
|
|
| 4. |
- Ericson, Stefan K., 1974-, et al.
(författare)
-
Analysis of two visual odometry systems for use in an agricultural field environment
- 2018
-
Ingår i: Biosystems Engineering. - London : Elsevier. - 1537-5110 .- 1537-5129. ; 166, s. 116-125
-
Tidskriftsartikel (refereegranskat)abstract
- This paper analyses two visual odometry systems for use in an agricultural field environment. The impact of various design parameters and camera setups are evaluated in a simulation environment. Four real field experiments were conducted using a mobile robot operating in an agricultural field. The robot was controlled to travel in a regular back-and-forth pattern with headland turns. The experimental runs were 1.8–3.1 km long and consisted of 32–63,000 frames. The results indicate that a camera angle of 75° gives the best results with the least error. An increased camera resolution only improves the result slightly. The algorithm must be able to reduce error accumulation by adapting the frame rate to minimise error. The results also illustrate the difficulties of estimating roll and pitch using a downward-facing camera. The best results for full 6-DOF position estimation were obtained on a 1.8-km run using 6680 frames captured from the forward-facing cameras. The translation error (x,y,z) is 3.76% and the rotational error (i.e., roll, pitch, and yaw) is 0.0482 deg m−1. The main contributions of this paper are an analysis of design option impacts on visual odometry results and a comparison of two state-of-the-art visual odometry algorithms, applied to agricultural field data.
|
|
| 5. |
- Ericson, Stefan, et al.
(författare)
-
Row-detection on an agricultural field using omnidirectional camera
- 2010
-
Ingår i: 2010 IEEE/RSJ international conference on intelligent robots and systems. - Piscataway, N.J. : IEEE Press. - 9781424466740 - 9781424466764 - 9781424466757 ; , s. 4982-4987
-
Konferensbidrag (refereegranskat)abstract
- This paper describes a method of detecting parallel rows on an agricultural field using an omnidirectional camera. The method works both on cameras with a fisheye lens and cameras with a catadioptric lens. A combination of an edge based method and a Hough transform method is suggested to find the rows. The vanishing point of several parallel rows is estimated using a second Hough transform. The method is evaluated on synthetic images generated with calibration data from real lenses. Scenes with several rows are produced, where each plant is positioned with a specified error. Experiments are performed on these synthetic images and on real field images. The result shows that good accuracy is obtained on the vanishing point once it is detected correctly. Further it shows that the edge based method works best when the rows consists of solid lines, and the Hough method works best when the rows consists of individual plants. The experiments also show that the combined method provides better detection than using the methods separately.
|
|
| 6. |
- Ericson, Stefan, et al.
(författare)
-
Stereo Visual Odometry for Mobile Robots on Uneven Terrain
- 2008
-
Ingår i: WCECS '08 Proceedings of the Advances in Electrical and Electronics Engineering - IAENG Special Edition of the World Congress on Engineering and Computer Science 2008. - Washington : IEEE Computer Society. - 9780769535555 - 9781424435456 ; , s. 150-157
-
Konferensbidrag (refereegranskat)abstract
- In this paper we present a stereo visual odometry system for mobile robots that is not sensitive to uneven terrain. Two cameras is mounted perpendicular to the ground and height and traveled distance are calculated using normalized cross correlation. A method for evaluating the system is developed, where flower boxes containing representative surfaces are placed in a metal-working lathe. The cameras are mounted on the carriage which can be positioned manually with 0.1 mm accuracy. Images are captured every 10 mm over 700 mm. The tests are performed on eight different surfaces representing real world situations. The resulting error is less than 0.6% of traveled distance on surfaces where the maximum height variation is measured to 96 mm. The variance is measured for eight test runs, total 5.6 m, to 0.040 mm. This accuracy is sufficient for crop-scale agricultural operations.
|
|
| 7. |
- Fan, Yuantao, 1989-, et al.
(författare)
-
Infrastructure Mapping in Well-Structured Environments Using MAV
- 2016
-
Ingår i: Lecture Notes in Computer Science. - Cham, Switzerland : Springer. - 0302-9743 .- 1611-3349. - 9783319403786 - 9783319403793 ; 9716, s. 116-126
-
Tidskriftsartikel (refereegranskat)abstract
- In this paper, we present a design of a surveying system for warehouse environment using low cost quadcopter. The system focus on mapping the infrastructure of surveyed environment. As a unique and essential parts of the warehouse, pillars from storing shelves are chosen as landmark objects for representing the environment. The map are generated based on fusing the outputs of two different methods, point cloud of corner features from Parallel Tracking and Mapping (PTAM) algorithm with estimated pillar position from a multi-stage image analysis method. Localization of the drone relies on PTAM algorithm. The system is implemented in Robot Operating System(ROS) and MATLAB, and has been successfully tested in real-world experiments. The result map after scaling has a metric error less than 20 cm. © Springer International Publishing Switzerland 2016.
|
|
| 8. |
- Gholami Shahbandi, Saeed, 1984-, et al.
(författare)
-
Modeling of a Large Structured Environment : With a Repetitive Canonical Geometric-Semantic Model
- 2014
-
Ingår i: Advances in Autonomous Robotics Systems. - Heidelberg : Springer. - 9783319104003 - 9783319104010 ; , s. 1-12
-
Konferensbidrag (refereegranskat)abstract
- AIMS project attempts to link the logistic requirements of an intelligent warehouse and state of the art core technologies of automation, by providing an awareness of the environment to the autonomous systems and vice versa. In this work we investigate a solution for modeling the infrastructure of a structured environment such as warehouses, by the means of a vision sensor. The model is based on the expected pattern of the infrastructure, generated from and matched to the map. Generation of the model is based on a set of tools such as closed-form Hough transform, DBSCAN clustering algorithm, Fourier transform and optimization techniques. The performance evaluation of the proposed method is accompanied with a real world experiment. © 2014 Springer International Publishing.
|
|
| 9. |
- Gholami Shahbandi, Saeed, 1984-, et al.
(författare)
-
Semi-Supervised Semantic Labeling of Adaptive Cell Decomposition Maps in Well-Structured Environments
- 2015
-
Ingår i: 2015 European Conference on Mobile Robots (ECMR). - Piscataway, NJ : IEEE Press.
-
Konferensbidrag (refereegranskat)abstract
- We present a semi-supervised approach for semantic mapping, by introducing human knowledge after unsupervised place categorization has been combined with an adaptive cell decomposition of an occupancy map. Place categorization is based on clustering features extracted from raycasting in the occupancy map. The cell decomposition is provided by work we published previously, which is effective for the maps that could be abstracted by straight lines. Compared to related methods, our approach obviates the need for a low-level link between human knowledge and the perception and mapping sub-system, or the onerous preparation of training data for supervised learning. Application scenarios include intelligent warehouse robots which need a heightened awareness in order to operate with a higher degree of autonomy and flexibility, and integrate more fully with inventory management systems. The approach is shown to be robust and flexible with respect to different types of environments and sensor setups. © 2015 IEEE
|
|
| 10. |
- Gholami Shahbandi, Saeed, 1984-, et al.
(författare)
-
Sensor Based Adaptive Metric-Topological Cell Decomposition Method for Semantic Annotation of Structured Environments
- 2014
-
Ingår i: 2014 13th International Conference on Control Automation Robotics & Vision (ICARCV). - Piscataway, NJ : IEEE Press. - 9781479951994 ; , s. 1771-1777
-
Konferensbidrag (refereegranskat)abstract
- A fundamental ingredient for semantic labeling is a reliable method for determining and representing the relevant spatial features of an environment. We address this challenge for planar metric-topological maps based on occupancy grids. Our method detects arbitrary dominant orientations in the presence of significant clutter, fits corresponding line features with tunable resolution, and extracts topological information by polygonal cell decomposition. Real-world case studies taken from the target application domain (autonomous forklift trucks in warehouses) demonstrate the performance and robustness of our method, while results from a preliminary algorithm to extract corridors, and junctions, demonstrate its expressiveness. Contribution of this work starts with the formulation of metric-topological surveying of environment, and a generic n-direction planar representation accompanied with a general method for extracting it from occupancy map. The implementation also includes some semantic labels specific to warehouse like environments. © 2014 IEEE.
|
|
