2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV) 2018
DOI: 10.1109/icarcv.2018.8581239
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Reciprocal Collision Avoidance for Nonholonomic Mobile Robots

Abstract: We present a method for deadlock-free and collisionfree navigation in a multi-robot system with nonholonomic robots. The problem is solved by quadratic programming and is applicable to most wheeled mobile robots with linear kinematic constraints. We introduce masked velocity and Masked Cooperative Collision Avoidance (MCCA) algorithm to encourage a fully decentralized deadlock avoidance behavior. To verify the method, we provide a detailed implementation and introduce heading oscillation avoidance for differen… Show more

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Cited by 9 publications
(3 citation statements)
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“…ORCA can only handle motion planning problems where each robot is isomorphic and does not have nonholonomic constraints. In [10], [11], researchers optimize the limitation of ORCA so that it can deal with more general task scenarios. It is worth noting that there are many prerequisites for the application of ORCA and its variants.…”
Section: A Related Workmentioning
confidence: 99%
“…ORCA can only handle motion planning problems where each robot is isomorphic and does not have nonholonomic constraints. In [10], [11], researchers optimize the limitation of ORCA so that it can deal with more general task scenarios. It is worth noting that there are many prerequisites for the application of ORCA and its variants.…”
Section: A Related Workmentioning
confidence: 99%
“…Such people attempt to remain close to other members of the group and aim for the same goal location. 25There are many further extentions to VOs to specialize movement and behaviors to account for a variety of agent and robot types, such as elliptical agents [25], holonomic movement [26], and non-holonomic movement [27] [28]. A further extension of particular interest is optimal reciprocal collision avoidance (ORCA).…”
Section: Introductionmentioning
confidence: 99%
“…Usually, the robot does not need to re-find the path to the final destination, since it is a time consumption process. Instead, the robot only needs to find a path among a small region which could enable the robot to bypass the obstacles by using some typically local motion planning approaches, such as dynamic window approach (DWA) [74,75], velocity obstacles [76,77], time-to-collision approaches [78][79][80], et al .…”
Section: Uwb/lidar Fusion For Autonomous Explorationmentioning
confidence: 99%