摘要
在人机共同作业过程中,由于机器人缺乏准确预测人运动意图的能力,人机难以实现安全、友好协作,导致人机协作效率低下.为对人机共同作业过程中操作者的运动意图进行预测,该文以人机共同搬运作业为例,根据人机协作运动的特点,提出了一种基于操作者的人手运动意图感知框架.主要包括两个方面:1)利用自回归方法对人手的运动轨迹进行预测,提出一种在人机共同作业中机器人运动轨迹规划方法,使机器人可以提前感知人的运动意图;2)在人手运动轨迹预测中引入方向补偿方法以降低人机之间的交互力.通过本文方法和卡尔曼滤波预测方法对比,实验表明,与没有运动轨迹预测相比,有运动轨迹预测时机器人受到的交互力降低了至少45.9%.与没有方向补偿相比,运动预测方法中加入方向补偿时,机器人受到的交互力降低了30.4%,轨迹预测误差的最大值降低了32.4%,平均误差也降低了6.8%.与卡尔曼滤波轨迹预测方法对比,交互力降低了52.2%.
During collaborative operations between humans and robots,the robot’s inability to accurately predict human motion intentions hampers the achievement of safe and friendly collaboration,resulting in inefficient human-robot collaboration.To predict the operator’s motion intentions during human-robot collaborative co-carrying,an operator-based framework for the perception of human hand motion intention is proposed in this paper.This framework primarily includes two aspects:1)using an autoregressive method to predict hand motion trajectories and proposing a robot motion trajectory planning method for human-robot collaborative operations,enabling the robot to anticipate human motion intentions;2)introducing a directional compensation method in hand motion trajectory prediction to reduce interaction forces between humans and robots.Experimental results show that compared to scenarios without motion intention prediction,the interactive forces on the robotic arm decrease by at least 45.9%when motion intention prediction is implemented.Furthermore,when directional compensation is introduced into the motion prediction method,a 30.4%decrease in interactive forces on the robotic arm is observed compared to scenarios without directional compensation.The maximum trajectory prediction error decreases by 32.4%,and the average error decreases by 6.8%.Compared to Kalman filtering trajectory prediction,interaction forces decreases by 52.2%.
作者
朱逸凡
罗晶
张超逸
曾超
庞牧野
ZHU Yifan;LUO Jing;ZHANG Chaoyi;ZENG Chao;PANG Muye(School of Automation,Wuhan University of Technology,Wuhan 430070,China;Chongqing Research Institute,Wuhan University of Technology,Chongqing 401135,China;Department of Computer Science,University of Liverpool,Liverpool L693BX,UK)
出处
《华中师范大学学报(自然科学版)》
北大核心
2025年第4期533-543,共11页
Journal of Central China Normal University:Natural Sciences
基金
国家自然科学基金项目(62203341)
湖北省自然科学基金项目(2024AFB614)
重庆市自然科学基金项目(CSTB2023NSCQ-MSX1078)
浙江省自然科学基金联合基金项目(LLSSZ25F030002)
武汉理工大学研究生教育教学改革研究项目(35400000).
关键词
人机协作
运动意图预测
自回归模型
方向补偿
human-robot collaboration
motion intention prediction
autoregressive model
directional compensation
