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.

受一些商用移动机器人的运动方式的启发，我们研究了机器人直线前进直到与环境边界发生碰撞的能力，在这种情况下它们可以旋转并再次前进。我们将其可视化为机器人“跳出”边界。我们定义了弹跳规则，以控制到达边界后机器人应如何重新定向，例如相对于碰撞前其前进方向或相对于边界法线的重新定向。然后，我们使用跳动可见性图表将计划生成为规则序列由多边形环境定义生成，同时假设我们在执行过程中不可避免地具有不确定性。可以询问我们的计划者以确定诸如达成目标集和巡逻（重复访问一系列目标）之类的任务的可行性。如果发现任务可行，则计划者会提供一系列不确定的交互规则，这些规则还提供有关机器人必须如何精确地执行计划才能成功的信息。我们还将展示如何计算稳定的循环轨迹，并使用它们来限制机器人位置的不确定性。