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- 저자 : Yushing Cheung (검색결과 2 건)
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Semi-Autonomous Collaborative Control for Multi-Weapon Multi-Target Pairing
Yushing Cheung,Jae H. Chung 제어로봇시스템학회 2010 제어로봇시스템학회 국제학술대회 논문집 Vol.2010 No.10
This paper focuses on developing a control method for a robotic single-master multi-slave (SMMS) system to cooperatively control mobile agents for multi-weapon multi-target pairing (WTP). Major components of the developed control method are potential field based leader-follower formation, compensation for operator-induced errors, and weapon-target pairings (WTP). A SMMS system has two subsystems, a single master and multi-slave robots. The master robot can transmit operator commands to the multi-slave robots which are a team of mobile manipulators to execute them while sensing environments. The multi-slave robots are divided into subgroups according to the number and types of weapons and targets for optimal effects. Each subgroup has a leader-follower architecture/ formation. The group leader is remotely controlled by a human operator to lead the leaders and followers of the subgroups. The transparency of the SMMS system is adjusted adaptively due to the compensation for operator-induced errors if they are detected. A sensor based auto-switching method is developed as a means to combine formation reconfiguration, collision avoidance, and motion control for reliability and robustness of the system. The WTP method is derived from the proven auction algorithm for a single target and is extended for multi-weapon multi-target cases, which optimizes effect-based weapon-target pairing based on a new heuristic algorithm. This is a novel approach that combines rule-based and function-based weapon-target pairing. The multi-weapon/ target pairing (MWTP) method is a weighted attack guidance table (WAGT), which includes the benefits of assigning weapon system combinations to targets. MWTP converges rapidly - as is the case for auction algorithms with integer benefits - but produces a suboptimal solution in general. Since MWTP represents a heuristic algorithm, further performance evaluation is anticipated in the future to verify the performance and the quality of the solution. A simulation study illustrates the efficacy of the proposed SMMS system for weapon-target pairing and target pursuit applications. In the simulation, the targets are assumed to be detected, identified, and geo-located by the operator and/or sensors. The team moves in an adaptive leader-follower formation to avoid obstacles if any and track targets as if the team was in a potential field. Each robot in the team is prioritized according to its functionality based on the types of weapons and targets, and subgroups are formed accordingly. Then, a robot in each subgroup is selected as the leader based on its proximity to the target and the weapon type. The subgroup leaders track the reference paths generated with respect to the positions of the group leader.
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