This paper presents a novel hybrid task priority-based motion planning algorithm of a space robot. The satellite attitude control task is defined as the primary task, while the leastsquares-based non-strict task prior...This paper presents a novel hybrid task priority-based motion planning algorithm of a space robot. The satellite attitude control task is defined as the primary task, while the leastsquares-based non-strict task priority solution of the end-effector plus the multi-constraint task is viewed as the secondary task. Furthermore, a null-space task compensation strategy in the joint space is proposed to derive the combination of non-strict and strict task-priority motion planning,and this novel combination is termed hybrid task priority control. Thus, the secondary task is implemented in the primary task＇s null-space. Besides, the transition of the state of multiple constraints between activeness and inactiveness will only influence the end-effector task without any effect on the primary task. A set of numerical experiments made in a real-time simulation system under Linux/RTAI shows the validity and feasibility of the proposed methodology.展开更多
Nowadays, robots generally have a variety of capabilities, which often form a coalition replacing human to work in dangerous environment, such as rescue, exploration, etc. In these operating conditions, the energy sup...Nowadays, robots generally have a variety of capabilities, which often form a coalition replacing human to work in dangerous environment, such as rescue, exploration, etc. In these operating conditions, the energy supply of robots usually cannot be guaranteed. If the energy resources of some robots are consumed too fast, the number of the future tasks of the coalition will be affected. This paper will develop a novel task allocation method based on Gini coefficient to make full use of limited energy resources of multi-robot system to maximize the number of tasks. At the same time, considering resources consumption,we incorporate the market-based allocation mechanism into our Gini coefficient-based method and propose a hybrid method,which can flexibly optimize the task completion number and the resource consumption according to the application contexts.Experiments show that the multi-robot system with limited energy resources can accomplish more tasks by the proposed Gini coefficient-based method, and the hybrid method can be dynamically adaptive to changes of the work environment and realize the dual optimization goals.展开更多
Task scheduling for electro-magnetic detection satellite is a typical combinatorial optimization problem. The count of constraints that need to be taken into account is of large scale. An algorithm combined integer pr...Task scheduling for electro-magnetic detection satellite is a typical combinatorial optimization problem. The count of constraints that need to be taken into account is of large scale. An algorithm combined integer programming with constraint programming is presented. This algorithm is deployed in this problem through two steps. The first step is to decompose the original problem into master and sub-problem using the logic-based Benders decomposition; then a circus combines master and sub-problem solving process together, and the connection between them is general Benders cut. This hybrid algorithm is tested by a set of derived experiments. The result is compared with corresponding outcomes generated by the strength Pareto evolutionary algorithm and the pure constraint programming solver GECODE, which is an open source software. These tests and comparisons yield promising effect.展开更多
针对巡飞弹群协同执行侦察、打击和评估的任务分配问题,考虑任务时序约束、目标属性异构特征以及支持多弹共同执行一个任务的需求,提出一种基于联合投标的一致性包拍卖算法(Joint-bidding-based Consensus Based Bundle Algorithm,JCBB...针对巡飞弹群协同执行侦察、打击和评估的任务分配问题,考虑任务时序约束、目标属性异构特征以及支持多弹共同执行一个任务的需求,提出一种基于联合投标的一致性包拍卖算法(Joint-bidding-based Consensus Based Bundle Algorithm,JCBBA),以实现异构任务分配。在构建弹群协同“察打评”任务分配问题的组合优化模型的基础上,基于CBBA架构,定制任务包构建机制、个体竞标策略和考虑联合投标的边际收益计算方法,实现无中心通信条件下时序任务协同分配的快速鲁棒求解。多场景仿真试验结果表明,JCBBA可以在满足多种约束的前提下实现时序约束任务的合理分配,性能对比试验结果表明JCBBA能够更好地权衡协同任务分配的求解时效性和结果最优性,求解耗时相比一致性联盟算法减少约40%。展开更多
基金supported in part by the National Program on Key Basic Research Project (No. 2013CB733103)the Program for New Century Excellent Talents in University (No. NCET-10-0058)
文摘This paper presents a novel hybrid task priority-based motion planning algorithm of a space robot. The satellite attitude control task is defined as the primary task, while the leastsquares-based non-strict task priority solution of the end-effector plus the multi-constraint task is viewed as the secondary task. Furthermore, a null-space task compensation strategy in the joint space is proposed to derive the combination of non-strict and strict task-priority motion planning,and this novel combination is termed hybrid task priority control. Thus, the secondary task is implemented in the primary task＇s null-space. Besides, the transition of the state of multiple constraints between activeness and inactiveness will only influence the end-effector task without any effect on the primary task. A set of numerical experiments made in a real-time simulation system under Linux/RTAI shows the validity and feasibility of the proposed methodology.
基金supported by the National High Technology Research and Development Program of China(863 Program)(2015AA015403)the National Natural Science Foundation of China(61404069,61401185)the Project of Education Department of Liaoning Province(LJYL052)
文摘Nowadays, robots generally have a variety of capabilities, which often form a coalition replacing human to work in dangerous environment, such as rescue, exploration, etc. In these operating conditions, the energy supply of robots usually cannot be guaranteed. If the energy resources of some robots are consumed too fast, the number of the future tasks of the coalition will be affected. This paper will develop a novel task allocation method based on Gini coefficient to make full use of limited energy resources of multi-robot system to maximize the number of tasks. At the same time, considering resources consumption,we incorporate the market-based allocation mechanism into our Gini coefficient-based method and propose a hybrid method,which can flexibly optimize the task completion number and the resource consumption according to the application contexts.Experiments show that the multi-robot system with limited energy resources can accomplish more tasks by the proposed Gini coefficient-based method, and the hybrid method can be dynamically adaptive to changes of the work environment and realize the dual optimization goals.
基金supported by the National Security Fundamental Research Foundation of China (61361)the National Natural Science Foundation of China (61104180)
文摘Task scheduling for electro-magnetic detection satellite is a typical combinatorial optimization problem. The count of constraints that need to be taken into account is of large scale. An algorithm combined integer programming with constraint programming is presented. This algorithm is deployed in this problem through two steps. The first step is to decompose the original problem into master and sub-problem using the logic-based Benders decomposition; then a circus combines master and sub-problem solving process together, and the connection between them is general Benders cut. This hybrid algorithm is tested by a set of derived experiments. The result is compared with corresponding outcomes generated by the strength Pareto evolutionary algorithm and the pure constraint programming solver GECODE, which is an open source software. These tests and comparisons yield promising effect.
文摘针对巡飞弹群协同执行侦察、打击和评估的任务分配问题,考虑任务时序约束、目标属性异构特征以及支持多弹共同执行一个任务的需求,提出一种基于联合投标的一致性包拍卖算法(Joint-bidding-based Consensus Based Bundle Algorithm,JCBBA),以实现异构任务分配。在构建弹群协同“察打评”任务分配问题的组合优化模型的基础上,基于CBBA架构,定制任务包构建机制、个体竞标策略和考虑联合投标的边际收益计算方法,实现无中心通信条件下时序任务协同分配的快速鲁棒求解。多场景仿真试验结果表明,JCBBA可以在满足多种约束的前提下实现时序约束任务的合理分配,性能对比试验结果表明JCBBA能够更好地权衡协同任务分配的求解时效性和结果最优性,求解耗时相比一致性联盟算法减少约40%。
