信息与控制2025，Vol.54Issue(4)：619-631,643,14.DOI:10.13976/j.cnki.xk.2024.2211
复杂场景下机械臂多动作协同抓取策略
Multi-action Cooperative Grasping Strategy for Robotic Arms in Complex Scenes
摘要
Abstract
In complex,uncertain real-world environments,challenges such as disorder,occlusion,and self-occlusion of grasped objects hinder robots from effectively perceiving scenes and executing pre-cise grasps.To tackle these issues,researchers have proposed an active visual framework to en-hance scene perception strategies.By coordinating viewpoint adjustments with grasping tasks,this approach aims to improve scene information acquisition and object separation.However,most cur-rent methods employ top-down actions,limiting the robot's scene perception capabilities.This study introduces an active visual perception and grasping coordination strategy in a 6-degree-of-freedom(6DoF)pose space.Utilizing deep reinforcement learning,we develop a viewpoint ad-justment network,a 4-degree-of-freedom(4DoF)grasping network,and a 6DoF grasping network to learn optimal collaborative strategies.Actions are determined using Q-functions and constraints to execute suitable primitive actions.To enhance scene perception,we propose a scene fusion method following viewpoint adjustment,which integrates information from multiple viewpoints into fixed-size height maps.Experiment results demonstrate an 8.93％increase in captured scene area compared to top-down methods in single viewpoint scenarios,providing comprehensive information for grasping tasks.In cluttered scenes containing ten target objects,the grasping success rate rea-ches 89.53％.Compared to the state-of-the-art VPG algorithm,our proposed method achieves a 12.02％increase in grasping success rate.关键词
深度强化学习/机械臂抓取/主动视觉感知/视点融合Key words
deep reinforcement learning/robotic manipulator grasping/active visual perception/viewpoint fusion分类
信息技术与安全科学引用本文复制引用
李德平,洪楷宣,柳宁,王高..复杂场景下机械臂多动作协同抓取策略[J].信息与控制,2025,54(4):619-631,643,14.基金项目
国家自然科学基金项目(62172188,61775172、62276114) （62172188,61775172、62276114）
韶关市科技计划项目(230615178031046) （230615178031046）
珠海市科技计划项目(2220004002542,2220004002325,ZH22017001210107PWC) （2220004002542,2220004002325,ZH22017001210107PWC）
