Path Tracking with Obstacle Avoidance for Pseudo-Omnidirectional Mobile Robots Using Convex Optimization
(2014) American Control Conference, 2014 p.517-524- Abstract
- We consider the problem of trajectory generation for time-optimal path tracking for the class of pseudo-omnidirectional mobile robots. An Euler-Lagrange model of the robot dynamics is derived, and by writing it on special form a convex reformulation of the path-tracking problem can be utilized. This enables the use and regeneration of time-optimal trajectories during runtime. The proposed approach also incorporates avoidance of moving obstacles, which are unknown a priori. Using sensor data, objects along the desired path are detected. Subsequently, a new path is planned and the corresponding time-optimal trajectory is found. The robustness of the method and its sensitivity to model errors are analyzed and discussed with extensive... (More)
- We consider the problem of trajectory generation for time-optimal path tracking for the class of pseudo-omnidirectional mobile robots. An Euler-Lagrange model of the robot dynamics is derived, and by writing it on special form a convex reformulation of the path-tracking problem can be utilized. This enables the use and regeneration of time-optimal trajectories during runtime. The proposed approach also incorporates avoidance of moving obstacles, which are unknown a priori. Using sensor data, objects along the desired path are detected. Subsequently, a new path is planned and the corresponding time-optimal trajectory is found. The robustness of the method and its sensitivity to model errors are analyzed and discussed with extensive simulation results. Moreover, we verify the approach by successful execution on a physical setup. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/4280557
- author
- Berntorp, Karl LU ; Olofsson, Björn LU and Robertsson, Anders LU
- organization
- publishing date
- 2014
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- [Host publication title missing]
- editor
- Alessandro, Astolfi
- pages
- 517 - 524
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- American Control Conference, 2014
- conference location
- Portland, OR, United States
- conference dates
- 2014-06-04 - 2014-06-06
- external identifiers
-
- wos:000346492601012
- scopus:84905711412
- ISSN
- 0743-1619
- project
- ENGROSS
- SMErobotics
- RobotLab LTH
- language
- English
- LU publication?
- yes
- id
- ae3fbca9-ee67-4420-87c8-7c2a7991ffc3 (old id 4280557)
- date added to LUP
- 2016-04-01 12:56:33
- date last changed
- 2023-04-24 22:03:59
@inproceedings{ae3fbca9-ee67-4420-87c8-7c2a7991ffc3,
abstract = {{We consider the problem of trajectory generation for time-optimal path tracking for the class of pseudo-omnidirectional mobile robots. An Euler-Lagrange model of the robot dynamics is derived, and by writing it on special form a convex reformulation of the path-tracking problem can be utilized. This enables the use and regeneration of time-optimal trajectories during runtime. The proposed approach also incorporates avoidance of moving obstacles, which are unknown a priori. Using sensor data, objects along the desired path are detected. Subsequently, a new path is planned and the corresponding time-optimal trajectory is found. The robustness of the method and its sensitivity to model errors are analyzed and discussed with extensive simulation results. Moreover, we verify the approach by successful execution on a physical setup.}},
author = {{Berntorp, Karl and Olofsson, Björn and Robertsson, Anders}},
booktitle = {{[Host publication title missing]}},
editor = {{Alessandro, Astolfi}},
issn = {{0743-1619}},
language = {{eng}},
pages = {{517--524}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
title = {{Path Tracking with Obstacle Avoidance for Pseudo-Omnidirectional Mobile Robots Using Convex Optimization}},
url = {{https://lup.lub.lu.se/search/files/3059284/4316431.pdf}},
year = {{2014}},
}