TY - JOUR
T1 - A visibility-based approach to computing non-deterministic bouncing strategies
AU - Nilles, Alexandra Q.
AU - Ren, Yingying
AU - Becerra, Israel
AU - LaValle, Steven M.
N1 - Funding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the NSF (grant numbers 1035345 and 1328018) and CONACyT (post-doctoral fellowship 277028).
Publisher Copyright:
© The Author(s) 2021.
PY - 2021/9
Y1 - 2021/9
N2 - Inspired by motion patterns of some commercially available mobile robots, we investigate the power of robots that move forward in straight lines until colliding with an environment boundary, at which point they can rotate in place and move forward again; we visualize this as the robot “bouncing” off boundaries. We define bounce rules governing how the robot should reorient after reaching a boundary, such as reorienting relative to its heading prior to collision, or relative to the normal of the boundary. We then generate plans as sequences of rules, using the bounce visibility graph generated from a polygonal environment definition, while assuming we have unavoidable non-determinism in our actuation. Our planner can be queried to determine the feasibility of tasks such as reaching goal sets and patrolling (repeatedly visiting a sequence of goals). If the task is found feasible, the planner provides a sequence of non-deterministic interaction rules, which also provide information on how precisely the robot must execute the plan to succeed. We also show how to compute stable cyclic trajectories and use these to limit uncertainty in the robot’s position.
AB - Inspired by motion patterns of some commercially available mobile robots, we investigate the power of robots that move forward in straight lines until colliding with an environment boundary, at which point they can rotate in place and move forward again; we visualize this as the robot “bouncing” off boundaries. We define bounce rules governing how the robot should reorient after reaching a boundary, such as reorienting relative to its heading prior to collision, or relative to the normal of the boundary. We then generate plans as sequences of rules, using the bounce visibility graph generated from a polygonal environment definition, while assuming we have unavoidable non-determinism in our actuation. Our planner can be queried to determine the feasibility of tasks such as reaching goal sets and patrolling (repeatedly visiting a sequence of goals). If the task is found feasible, the planner provides a sequence of non-deterministic interaction rules, which also provide information on how precisely the robot must execute the plan to succeed. We also show how to compute stable cyclic trajectories and use these to limit uncertainty in the robot’s position.
KW - Underactuated robots
KW - dynamics
KW - motion control
KW - motion planning
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U2 - 10.1177/0278364921992788
DO - 10.1177/0278364921992788
M3 - Article
AN - SCOPUS:85101041665
SN - 0278-3649
VL - 40
SP - 1196
EP - 1211
JO - International Journal of Robotics Research
JF - International Journal of Robotics Research
IS - 10-11
ER -