A Convex Approach to Path Tracking with Obstacle Avoidance for Pseudo-Omnidirectional Vehicles
(2015) In Technical Reports TFRT-7643- Abstract
- This report addresses the related problems of trajectory generation and time-optimal path tracking with online obstacle avoidance. We consider the class of four-wheeled vehicles with independent steering and driving on each wheel, also referred to as pseudo-omnidirectional vehicles. Appropriate approximations of the dynamic model enable a convex reformulation of the path-tracking problem. Using the precomputed trajectories together with model predictive control that utilizes feedback from the estimated global pose, provides robustness to model uncertainty and disturbances. The considered approach also incorporates avoidance of a priori unknown moving obstacles by local online replanning. We verify the approach by successful execution on a... (More)
- This report addresses the related problems of trajectory generation and time-optimal path tracking with online obstacle avoidance. We consider the class of four-wheeled vehicles with independent steering and driving on each wheel, also referred to as pseudo-omnidirectional vehicles. Appropriate approximations of the dynamic model enable a convex reformulation of the path-tracking problem. Using the precomputed trajectories together with model predictive control that utilizes feedback from the estimated global pose, provides robustness to model uncertainty and disturbances. The considered approach also incorporates avoidance of a priori unknown moving obstacles by local online replanning. We verify the approach by successful execution on a pseudo-omnidirectional mobile robot, and compare it to an existing algorithm. The result is a significant decrease in the time for completing the desired path. In addition, the method allows a smooth velocity trajectory while avoiding intermittent stops in the path execution. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/8232521
- author
- Olofsson, Björn LU ; Berntorp, Karl LU and Robertsson, Anders LU
- organization
- publishing date
- 2015
- type
- Book/Report
- publication status
- published
- subject
- in
- Technical Reports TFRT-7643
- publisher
- Department of Automatic Control, Lund Institute of Technology, Lund University
- ISSN
- 0280-5316
- project
- SMErobotics
- RobotLab LTH
- language
- English
- LU publication?
- yes
- id
- e94a2763-95d5-4ab7-938c-561803015f07 (old id 8232521)
- date added to LUP
- 2016-04-01 13:06:55
- date last changed
- 2024-06-04 15:07:11
@techreport{e94a2763-95d5-4ab7-938c-561803015f07, abstract = {{This report addresses the related problems of trajectory generation and time-optimal path tracking with online obstacle avoidance. We consider the class of four-wheeled vehicles with independent steering and driving on each wheel, also referred to as pseudo-omnidirectional vehicles. Appropriate approximations of the dynamic model enable a convex reformulation of the path-tracking problem. Using the precomputed trajectories together with model predictive control that utilizes feedback from the estimated global pose, provides robustness to model uncertainty and disturbances. The considered approach also incorporates avoidance of a priori unknown moving obstacles by local online replanning. We verify the approach by successful execution on a pseudo-omnidirectional mobile robot, and compare it to an existing algorithm. The result is a significant decrease in the time for completing the desired path. In addition, the method allows a smooth velocity trajectory while avoiding intermittent stops in the path execution.}}, author = {{Olofsson, Björn and Berntorp, Karl and Robertsson, Anders}}, institution = {{Department of Automatic Control, Lund Institute of Technology, Lund University}}, issn = {{0280-5316}}, language = {{eng}}, series = {{Technical Reports TFRT-7643}}, title = {{A Convex Approach to Path Tracking with Obstacle Avoidance for Pseudo-Omnidirectional Vehicles}}, url = {{https://lup.lub.lu.se/search/files/3166114/8411067.pdf}}, year = {{2015}}, }