论文标题
强大的机器人辅助电视通过意图不确定性的计划
Robust Robot-assisted Tele-grasping Through Intent-Uncertainty-Aware Planning
论文作者
论文摘要
在远程流动方面，研究主要集中在目标临近，我们通过推进共享控制技术来应对更具挑战性的对象操纵任务。由于特定的操纵任务的精细运动约束要求，适当地操纵对象是具有挑战性的。尽管这些运动限制对于任务成功至关重要，但在观察模棱两可的人类运动时，它们通常是微妙的。人和机器人手之间的不同机构问题和身体差异带来了额外的不确定性，进一步夸大了对象操纵任务的并发症。此外，缺乏计划和建模技术，可以有效地结合人类和机器人的运动输入，同时考虑人类意图的歧义。为了克服这一挑战，我们建立了一个多任务机器人掌握模型，并开发了一种意图 - 意识到的抓紧计划者，以产生强大的掌握姿势，鉴于人类的意图推断输入模棱两可。通过这些经过验证的建模和计划技术，预计将在实际的远程触发场景中扩展遥控机器人的功能和采用。
In teleoperation, research has mainly focused on target approaching, where we deal with the more challenging object manipulation task by advancing the shared control technique. Appropriately manipulating an object is challenging due to the fine motion constraint requirements for a specific manipulation task. Although these motion constraints are critical for task success, they often are subtle when observing ambiguous human motion. The disembodiment problem and physical discrepancy between the human and robot hands bring additional uncertainty, further exaggerating the complications of the object manipulation task. Moreover, there is a lack of planning and modeling techniques that can effectively combine the human and robot agents' motion input while considering the ambiguity of the human intent. To overcome this challenge, we built a multi-task robot grasping model and developed an intent-uncertainty-aware grasp planner to generate robust grasp poses given the ambiguous human intent inference inputs. With these validated modeling and planning techniques, it is expected to extend teleoperated robots' functionality and adoption in practical telemanipulation scenarios.
