用图搜索与可达性地图实现人形机器人高效抓取搬运规划
Humanoid Loco-manipulation Planning based on Graph Search and Reachability Maps
- 将步态与抓取顺序建模为图搜索问题，灵活表达协同动作
- 通过动态更新可达性地图，快速评估机器人与物体运动的交互
- 适用于需重新抓取的复杂操作，如滚筒搬运任务
本文提出一种高效且高度通用的人形机器人走动-操作规划方法。走动-操作规划是人形机器人自主完成物体搬运的关键技术。我们将步态与抓取的交替与序列规划建模为图搜索问题，引入一种新的转移模型，可灵活表示走动-操作行为。该转移模型通过根据机器人和物体的运动快速重定位与切换可达性地图，实现高效评估。我们在多个走动-操作场景中验证了该方法，例如需要重新抓取的滚筒滚动操作，系统能自动规划出完整运动轨迹。
原文摘要 · Abstract (English)
In this letter, we propose an efficient and highly versatile loco-manipulation planning for humanoid robots. Loco-manipulation planning is a key technological brick enabling humanoid robots to autonomously perform object transportation by manipulating them. We formulate planning of the alternation and sequencing of footsteps and grasps as a graph search problem with a new transition model that allows for a flexible representation of loco-manipulation. Our transition model is quickly evaluated by relocating and switching the reachability maps depending on the motion of both the robot and object. We evaluate our approach by applying it to loco-manipulation use-cases, such as a bobbin rolling operation with regrasping, where the motion is automatically planned by our framework.
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