The paper is concerned with the dynamic tracking problem of SNAP orchards harvesting robots in the presence of multiple uncalibrated model parameters in the application of dwarf culture orchards harvest. A new hybrid visual servoing adaptive tracking controller and three adaptive laws are proposed to guarantee harvesting robots to finish the dynamic harvesting task and the adaption to unknown parameters including camera intrinsic and extrinsic model and robot dynamics. By the Lyapunov theory, asymptotic convergence of the closed-loop system with the proposed control scheme is rigorously proven. Experimental and simulation results have been conducted to verify the performance of the proposed control scheme. The results demonstrate its effectiveness and superiority.
翻译:论文关注SNAP果园采集机器人动态跟踪问题,在应用侏儒文化果园收获时,存在多种未经校准的模式参数,提出了一个新的混合视觉随机跟踪控制器和三项适应性法律,以保障采集机器人完成动态采集任务,并适应未知参数,包括照相机内在和外部模型和机器人动态。根据Lyapunov理论,闭环系统与拟议控制计划的无症状融合得到了严格证明。已经进行了实验和模拟结果,以核实拟议控制计划的绩效。结果证明了其有效性和优越性。