A Cartesian Platform for Cooperative Multi-Robot Manipulation Tasks

被引:0
作者
Muller, Silvio
Ilic, Stefan
Scamarcio, Vincenzo
Hughes, Josie
机构
来源
2023 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS) | 2023年
基金
欧盟地平线“2020”;
关键词
ROBOTIC MANIPULATION;
D O I
10.1109/IROS55552.2023.10342469
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
For many manipulation tasks in environments such as laboratory or a kitchen, the presence of two robot arms is important to enable collaborative tasks requiring two arms (e.g. lid removal or tool use) or to improve the efficiency of scheduling of tasks. Currently, the development of multi-arm manipulation solutions has largely focused on 6 degrees of freedom articulated robot arms. However, cartesian robots have many advantages, including their precision, reliability, efficiency, and simple path planning. By developing a cartesian platform such that the end effectors of two mirrored systems can interact freely without collisions in 5 degrees of freedom, we can leverage the advantages of cartesian robots (high precision, simple planning, and low-cost hardware) and show robot cooperation. We equip each robot with end-effectors with different skills to increase the range of tasks the robots can cooperatively complete. To exploit this robotic hardware, we have developed a task-allocation and path-planning algorithm that enables these two mirror robots to work together to solve tasks collaboratively, exploiting the different skills and workspace of the two robots. We show how this robot can be used for cooperative tasks in lab automation, including pick and place, unscrewing vial caps, liquid pouring, and weighing. These demonstrate the feasibility and capabilities of the proposed robotic system for cooperative automation using cartesian robots.
引用
收藏
页码:10082 / 10087
页数:6
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