{"title":"Online Capability Based Task Allocation of Cooperative Manipulators","authors":"Keshab Patra, Arpita Sinha, Anirban Guha","doi":"10.1007/s10846-024-02050-1","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":54794,"journal":{"name":"Journal of Intelligent & Robotic Systems","volume":"163 1","pages":""},"PeriodicalIF":3.1000,"publicationDate":"2024-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Intelligent & Robotic Systems","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s10846-024-02050-1","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
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.
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.).