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Theory and experiments in autonomous sensor-based motion planning with applications for flight planetary microrovers.

机译：基于自主传感器的运动计划中的理论和实验及其在飞行行星微粗纱机中的应用。

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With the success of Mars Pathfinder's Sojourner rover, a new era of planetary exploration has opened, with demand for highly capable mobile robots. These robots must be able to traverse long distances over rough, unknown terrain autonomously, under severe resource constraints. Much prior work in mobile robot path planning has been based on assumptions that are not truly applicable to navigation through planetary terrains. Based on the author's firsthand experience with the Mars Pathfinder mission, this work reviews issues which are critical for successful autonomous navigation of planetary rovers. No current methodology addresses all of these constraints. We next develop the sensor-based “Wedgebug” motion-planning algorithm. This algorithm is complete, correct, requires minimal memory for storage of its world model, and uses only on-board sensors, which are guided by the algorithm to efficiently sense only the data needed for motion planning, while avoiding unnecessary robot motion. The planner has the additional advantage of producing locally-optimal paths, and is suitable for robots with a field-of-view limited in both downrange and angular scope, for a variety of applications including planetary navigation. This work includes the proof of completeness and correctness of the Wedgebug algorithm, and in particular provides a corrected, detailed proof of a key result required for the proof of completeness of the Wedgebug algorithm (and for the TangentBug algorithm which inspired this approach). In addition, we extend this result to a broader class of environments. The implementation of a version of Wedgebug, called “RoverBug,” on the Rocky7 Mars Rover prototype at the Jet Propulsion Laboratory (JPL) is described, and experimental results from operation in simulated martian terrain are presented.
机译：随着火星探路者号的“旅居者”漫游者的成功，开启了行星探索的新纪元，这需要高性能的移动机器人。这些机器人必须能够在严峻的资源限制下，在崎unknown不平的未知地形上自动穿越很长一段距离。移动机器人路径规划中的许多先前工作都是基于并非真正适用于在行星地形中导航的假设。根据作者在火星探路者任务中的第一手经验，本文回顾了对成功完成行星漫游车自主导航至关重要的问题。当前没有方法可解决所有这些限制。接下来，我们将开发基于传感器的“ Wedgebug”运动计划算法。该算法是完整，正确的，只需要最少的内存即可存储其世界模型，并且仅使用板载传感器，该传感器在算法的引导下可以有效地仅感测运动计划所需的数据，同时避免不必要的机器人运动。该计划器具有产生局部最优路径的附加优势，并且适用于在范围缩小和角度范围均受限的视场的机器人，适用于包括行星导航在内的各种应用。这项工作包括Wedgebug算法的完整性和正确性的证明，尤其是为Wedgebug算法（以及启发该方法的TangentBug算法）的完整性证明所需的关键结果提供了校正的详细证明。此外，我们将此结果扩展到更广泛的环境中。描述了在喷气推进实验室（JPL）的Rocky7火星探测器原型上名为“ RoverBug”的Wedgebug版本的实现，并给出了在模拟火星地形中运行的实验结果。

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