Adaptive Visual Servo Control of Robotic Harvesting Systems

Harvesting efficiency is a critical factor in determining whether robotic harvesting can be economically superior to hand picking. One practical challenge in robotic harvesting is to grasp a moving fruit, where unsuccessful pick cycles may result in lower harvesting efficiency. The fruit motion can be due to exogenous disturbances such as wind gust, canopy unloading, and particularly, fruit detachment forces. In this paper, an adaptive visual servo control law is presented to estimate and subsequently compensate the unknown time-varying fruit motion. The fruit motion in the image plane and along the optical axis is modeled as a second-order spring-mass system. The unknown parameters of fruit motion are identified using an adaptive parameter update law, and a robust feedback term is included in the control law to account for modeling uncertainties. Lyapunov-based stability analysis guarantees uniformly ultimately bounded regulation of the robot to the fruit position. Simulation results are provided to verify the feasibility of the developed controller.