Pushing in the Dark: A Reactive Pushing Strategy for Mobile Robots Using Tactile Feedback
arxiv(2024)
摘要
For mobile robots, navigating cluttered or dynamic environments often
necessitates non-prehensile manipulation, particularly when faced with objects
that are too large, irregular, or fragile to grasp. The unpredictable behavior
and varying physical properties of these objects significantly complicate
manipulation tasks. To address this challenge, this manuscript proposes a novel
Reactive Pushing Strategy. This strategy allows a mobile robot to dynamically
adjust its base movements in real-time to achieve successful pushing maneuvers
towards a target location. Notably, our strategy adapts the robot motion based
on changes in contact location obtained through the tactile sensor covering the
base, avoiding dependence on object-related assumptions and its modeled
behavior. The effectiveness of the Reactive Pushing Strategy was initially
evaluated in the simulation environment, where it significantly outperformed
the compared baseline approaches. Following this, we validated the proposed
strategy through real-world experiments, demonstrating the robot capability to
push objects to the target points located in the entire vicinity of the robot.
In both simulation and real-world experiments, the object-specific properties
(shape, mass, friction, inertia) were altered along with the changes in target
locations to assess the robustness of the proposed method comprehensively.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要