Revised Control Barrier Function with Sensing of Threats from Relative Velocity Between Humans and Mobile Robots

The mobile robot, which comprises a mobile platform and a robotic arm, has been widely adopted in industrial automation. Existing safe control methods with real-time trajectory alternation face difficulties in efficiently identifying threats from fast relative motion between humans and robots, causing hazards in environments of dense human-robot coexistence. This work firstly builds a safe mobile robot control framework in the kinematic sense. Secondly, the proximity between parts of a human and a mobile robot is efficiently solved by convex programming with parametric description of skew line segments. It is also no longer required to perform case-by-case analysis of skew line segments' relative pose in space. Thirdly, a novel threatening index is proposed to select the most threatened human parts based on mutual projection of human-robot relative velocity and their common normal vector. Eventually, this index is incorporated into the safety constraint, showing the improved safe control performance in the simulated human-mobile robot coexistence scenario.

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Publication Details

Journal
Sensors
Published
2025-06-27
DOI
https://doi.org/10.3390/s25134005
Primary Topic
Robot Manipulation and Learning
Type
article
Field-Weighted Citation Impact
0.00

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article

Revised Control Barrier Function with Sensing of Threats from Relative Velocity Between Humans and Mobile Robots

Guilin Yang, Xiangjie Kong, Zihan Zeng, Xiaojuan Li et al.
Sensors
Robot Manipulation and Learning
article

Revised Control Barrier Function with Sensing of Threats from Relative Velocity Between Humans and Mobile Robots

Guilin Yang, Xiangjie Kong, Zihan Zeng, Xiaojuan Li, Silu Chen, Chi Zhang
article en

Abstract

The mobile robot, which comprises a mobile platform and a robotic arm, has been widely adopted in industrial automation. Existing safe control methods with real-time trajectory alternation face difficulties in efficiently identifying threats from fast relative motion between humans and robots, causing hazards in environments of dense human-robot coexistence. This work firstly builds a safe mobile robot control framework in the kinematic sense. Secondly, the proximity between parts of a human and a mobile robot is efficiently solved by convex programming with parametric description of skew line segments. It is also no longer required to perform case-by-case analysis of skew line segments' relative pose in space. Thirdly, a novel threatening index is proposed to select the most threatened human parts based on mutual projection of human-robot relative velocity and their common normal vector. Eventually, this index is incorporated into the safety constraint, showing the improved safe control performance in the simulated human-mobile robot coexistence scenario.

SensorsVol. 25(13)
Chinese Academy of Sciences (CN), Ningbo Institute of Industrial Technology (CN), Xinjiang University (CN)
National Natural Science Foundation of China, Major Research Plan, Natural Science Foundation of Zhejiang Province
Openalex Percentile: Top 83%
Robot Manipulation and Learning
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