Online Capability Based Task Allocation of Cooperative Manipulators

IF 3.1 4区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Journal of Intelligent & Robotic Systems Pub Date : 2024-01-25 DOI:10.1007/s10846-024-02050-1
Keshab Patra, Arpita Sinha, Anirban Guha
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Abstract

The cooperative manipulator group can accomplish complex and heavy payload tasks of object manipulation and transportation compared to a single manipulator. Effective coordination is crucial for cooperative task accomplishments. Multi-manipulator task distribution is highly complex because of the varying dynamic capabilities of the manipulators. We have introduced a novel fastest technique to quantify the dynamic task capability of the cooperative manipulator by scalar quantity and allocate the task accordingly. The scalar quantity determines the capability of applying an external wrench by end effector (EE) in line with the required wrench at the center of mass of the manipulating object. This quantity helps to diminish tracking errors in object manipulations or transportation and actuator saturation avoidance. The task distribution among the members is in proportion to their computed dynamic capability to ensure equal priority to the individual manipulators. The proposed task distribution formulation ensures the minimum magnitude of wrench interaction at the grasp point and the minimum internal wrench build-up in the object. Several physical simulation results assure trajectory tracking performance with the proposed task capability metric. The same metric aids in identifying the least capable manipulator, rearranging members for better performance, and deciding the required number of manipulators in the manipulator group.

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基于能力的合作机械手在线任务分配
与单个机械手相比,合作机械手小组可以完成复杂而繁重的物体操作和运输任务。有效的协调对于合作完成任务至关重要。由于机械手的动态能力各不相同,多机械手任务分配非常复杂。我们引入了一种新颖的最快技术,通过标量量化合作机械手的动态任务能力,并据此分配任务。标量决定了末端效应器(EE)在操纵物体的质心处根据所需的扳手施加外部扳手的能力。这个量有助于减少物体操纵或运输过程中的跟踪误差,并避免致动器饱和。各成员之间的任务分配与其计算的动态能力成比例,以确保各机械手具有同等的优先权。所提出的任务分配方案可确保抓取点的扳手相互作用量最小,物体内部的扳手积聚量最小。一些物理仿真结果确保了使用所提出的任务能力指标进行轨迹跟踪的性能。该指标还有助于识别能力最弱的机械手,重新安排成员以提高性能,以及决定机械手组中所需的机械手数量。
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来源期刊
Journal of Intelligent & Robotic Systems
Journal of Intelligent & Robotic Systems 工程技术-机器人学
CiteScore
7.00
自引率
9.10%
发文量
219
审稿时长
6 months
期刊介绍: The Journal of Intelligent and Robotic Systems bridges the gap between theory and practice in all areas of intelligent systems and robotics. It publishes original, peer reviewed contributions from initial concept and theory to prototyping to final product development and commercialization. On the theoretical side, the journal features papers focusing on intelligent systems engineering, distributed intelligence systems, multi-level systems, intelligent control, multi-robot systems, cooperation and coordination of unmanned vehicle systems, etc. On the application side, the journal emphasizes autonomous systems, industrial robotic systems, multi-robot systems, aerial vehicles, mobile robot platforms, underwater robots, sensors, sensor-fusion, and sensor-based control. Readers will also find papers on real applications of intelligent and robotic systems (e.g., mechatronics, manufacturing, biomedical, underwater, humanoid, mobile/legged robot and space applications, etc.).
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