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基于时间间隔的人类共享室内环境中四轮独立转向移动机器人碰撞检测

Time-Interval-Based Collision Detection for 4WIS Mobile Robots in Human-Shared Indoor Environments.

作者信息

Kim Seungmin, Jang Hyunseo, Ha Jiseung, Lee Daekug, Ha Yeongho, Song Youngeun

机构信息

Department of Autonomous Mobility, Korea University, Sejong 2511, Republic of Korea.

Mobile Robotics Research and Development Center, FieldRo Co., Ltd., Sejong 2511, Republic of Korea.

出版信息

Sensors (Basel). 2025 Jan 31;25(3):890. doi: 10.3390/s25030890.

DOI:10.3390/s25030890
PMID:39943529
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11819964/
Abstract

The recent growth in e-commerce has significantly increased the demand for indoor delivery solutions, highlighting challenges in last-mile delivery. This study presents a time-interval-based collision detection method for Four-Wheel Independent Steering (4WIS) mobile robots operating in human-shared indoor environments, where traditional path following algorithms often create unpredictable movements. By integrating kinematic-based robot trajectory calculation with LiDAR-based human detection and Kalman filter-based prediction, our system enables more natural robot-human interactions. Experimental results demonstrate that our parallel driving mode achieves superior human detection performance compared to conventional Ackermann steering, particularly during cornering and high-speed operations. The proposed method's effectiveness is validated through comprehensive experiments in realistic indoor scenarios, showing its potential for improving the efficiency and safety of indoor autonomous navigation systems.

摘要

最近电子商务的发展显著增加了对室内配送解决方案的需求，凸显了最后一英里配送中的挑战。本研究提出了一种基于时间间隔的碰撞检测方法，用于在人类共享室内环境中运行的四轮独立转向（4WIS）移动机器人，在这种环境中传统的路径跟踪算法往往会产生不可预测的运动。通过将基于运动学的机器人轨迹计算与基于激光雷达的人体检测和基于卡尔曼滤波器的预测相结合，我们的系统实现了更自然的人机交互。实验结果表明，与传统的阿克曼转向相比，我们的平行驱动模式在人体检测性能上更优，尤其是在转弯和高速运行时。通过在实际室内场景中的综合实验验证了所提方法的有效性，表明其在提高室内自主导航系统效率和安全性方面的潜力。

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MPC-based high-speed trajectory tracking for 4WIS robot.基于模型预测控制的四轮独立转向机器人高速轨迹跟踪
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