首页|Studies Conducted at Shanghai Jiao Tong University on Robotics Recently Reported (Kinematic Performance-oriented Tool Orientation Optimization for a Hybrid Mach ining Robot In Five-axis Ballend Milling)

Studies Conducted at Shanghai Jiao Tong University on Robotics Recently Reported (Kinematic Performance-oriented Tool Orientation Optimization for a Hybrid Mach ining Robot In Five-axis Ballend Milling)

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Fresh data on Robotics are presented i n a new report. According to news originating from Shanghai, People's Republic o f China, by NewsRx correspondents, research stated, "Five-axis hybrid robots are more extensively used in the machining of complex parts, owing to their high dy namic performance and flexible attitude adjustment. Ball-end milling is widely e mployed in sculptured surface machining." Financial support for this research came from National Natural Science Foundatio n of China (NSFC). Our news journalists obtained a quote from the research from Shanghai Jiao Tong University, "The tool orientation can be adjusted for enhanced machining efficie ncy and superior cutting performance. However, hybrid robots' complex kinematic structures raise challenges to tool orientation planning. To generate a smooth t oolpath that has good cutting performance and satisfies all the geometric and me chanical constraints, a tool orientation optimization model is presented. The we ighted sum of the joint kinematic performance index and the effective tool diame ter indexes are taken as the objective function. By constructing the robot works pace in advance, the computation in the generation of feasible tool orientation regions is reduced. The feasible orientation regions are further simplified as l inear inequality constraints which are updated during iteration. In each iterati on, the initial nonconvex optimization problem is locally approximated by a conv ex problem and solved by quadratic programming (QP)."

ShanghaiPeople's Republic of ChinaAs iaEmerging TechnologiesMachine LearningNano-robotRobotRoboticsShangh ai Jiao Tong University

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Oct.9)