规划弹跳轨迹：碰撞容忍型机器人的反射类方法

中文摘要 AI 辅助

机器人导航方法往往倾向于避免接触，因此会搜索无碰撞轨迹。然而，对于具有高惯性和有限机动性的机器人来说，即使与周围表面的交互可以被安全利用，避免接触也可能需要大量的转向力和时间。在本文中，我们开发了一种规划方法，该方法有意地利用受控的墙壁反射来生成比纯无碰撞运动更容易执行且更高效的轨迹。我们考虑在允许移动机器人从周围表面弹开的平面环境中进行导航。为了表示由此产生的替代方案，我们构建了一个反射增强状态图，其中路径根据用于反射的墙壁序列被划分为不同的类别。这种表示使得能够系统地枚举反射策略，并识别每个类别中成本最低的路径。我们表明，尽管反射路径不可能比最短的无碰撞路径更短，但它可以通过用受控的环境交互替代昂贵的航向变化来减少执行时间和驱动力。规划的轨迹使用考虑接触的基于采样的控制器以及机器人的完整动力学来执行。在我们的实验中，我们证明了在我们的模拟测试场景中，最佳反射类可以减少时间和控制力。我们的结果表明，受控接触可以提供动态上有利的导航策略，而这些策略被传统的避碰公式所排除。

英文摘要

Robot navigation methods tend to avoid contact, and consequently search for collision-free trajectories. For robots with high inertia and limited maneuverability, however, avoiding contact can require substantial steering effort and time, even when interactions with surrounding surfaces could be safely exploited. In this paper, we develop a planning method that deliberately uses controlled wall reflections to generate trajectories that can be easier and more efficient to execute than purely collision-free motion. We consider planar navigation in environments where a mobile robot is permitted to bounce off surrounding surfaces. To represent the resulting alternatives, we construct a reflection-augmented state graph in which paths are partitioned into distinct classes according to the sequence of walls used for reflection. This representation enables systematic enumeration of reflection strategies and identification of the lowest-cost path within each class. We show that, although a reflecting path cannot be shorter than the shortest collision-free path, it can reduce execution time and actuation effort by replacing costly changes in heading with controlled environmental interactions. The planned trajectories are executed using a contact-aware sampling-based controller with the robot's full dynamics. In our experiments, we demonstrate that in our simulated test scenario, the best reflecting class can reduce time and control effort. Our results show that controlled contact can provide dynamically advantageous navigation strategies that are excluded by conventional collision-avoidance formulations.

发表机构

• Lehigh University（理海大学）

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