Hybrid Visual Servoing Tracking Control of Uncalibrated Robotic Systems for Dynamic Dwarf Culture Orchards Harvest

TL;DR

This paper introduces a hybrid visual servoing adaptive control method for uncalibrated robotic systems to improve dynamic harvesting in dwarf culture orchards, ensuring accurate tracking despite unknown parameters.

Contribution

A novel hybrid visual servoing adaptive control scheme with three adaptive laws for uncalibrated robots in orchard harvesting is proposed, with proven stability and superior performance.

Findings

Effective in handling uncalibrated parameters

Proven asymptotic convergence via Lyapunov theory

Demonstrated superior performance through experiments

Abstract

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.