Adaptive Vision-Based Control of Redundant Robots with Null-Space Interaction for Human-Robot Collaboration
Xiangjie Yan, Chen Chen, and Xiang Li

TL;DR
This paper introduces an adaptive vision-based control scheme for redundant robots that enhances human-robot collaboration by enabling autonomous task execution and safe interaction without prior environment calibration.
Contribution
It proposes a novel control approach combining task space and null space control for redundant robots, improving safety and adaptability in human-robot collaboration.
Findings
The control scheme ensures stable and convergent task execution.
Experimental validation with AR-guided robots demonstrates effectiveness.
The method handles unknown environments and human interactions safely.
Abstract
Human-robot collaboration aims to extend human ability through cooperation with robots. This technology is currently helping people with physical disabilities, has transformed the manufacturing process of companies, improved surgical performance, and will likely revolutionize the daily lives of everyone in the future. Being able to enhance the performance of both sides, such that human-robot collaboration outperforms a single robot/human, remains an open issue. For safer and more effective collaboration, a new control scheme has been proposed for redundant robots in this paper, consisting of an adaptive vision-based control term in task space and an interactive control term in null space. Such a formulation allows the robot to autonomously carry out tasks in an unknown environment without prior calibration while also interacting with humans to deal with unforeseen changes (e.g.,…
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Taxonomy
TopicsRobot Manipulation and Learning · Teleoperation and Haptic Systems · Social Robot Interaction and HRI
