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

**Authors:** Zihan Zeng, Silu Chen, Xiangjie Kong, Xiaojuan Li, Chi Zhang, Guilin Yang

PMC · DOI: 10.3390/s25134005 · Sensors (Basel, Switzerland) · 2025-06-27

## TL;DR

This paper introduces a new control method for mobile robots to better detect and avoid threats from fast human movements in shared workspaces.

## Contribution

A novel threatening index is proposed to improve safe control by incorporating relative velocity and spatial proximity analysis.

## Key findings

- A kinematic control framework was developed for safer human-robot coexistence.
- Convex programming efficiently solves proximity between humans and robots without case-by-case analysis.
- The new threatening index improves safety performance in simulated scenarios.

## 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.

## Full-text entities

- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

_Full body text omitted from this summary view._ Fetch the complete paper as Markdown: https://tomesphere.com/paper/PMC12251740/full.md

## Figures

9 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12251740/full.md

## References

41 references — full list in the complete paper: https://tomesphere.com/paper/PMC12251740/full.md

---
Source: https://tomesphere.com/paper/PMC12251740