Hybrid Visual Servoing Tracking Control of Uncalibrated Robotic Systems for Dynamic Dwarf Culture Orchards Harvest
This addresses the challenge of uncalibrated robotic harvesting in dynamic orchard environments, though it appears incremental as it builds on existing visual servoing and adaptive control methods.
The paper tackled the dynamic tracking problem for SNAP orchards harvesting robots with multiple uncalibrated parameters in dwarf culture orchards, proposing a hybrid visual servoing adaptive tracking controller that achieved asymptotic convergence and demonstrated effectiveness in experiments and simulations.
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.