A Model-Free Extremum-Seeking Approach to Autonomous Excavator Control Based on Output Power Maximization

Abstract

A new approach to autonomous excavator control that allows the machine to adapt to unknown soil properties is presented. Unlike traditional force control or trajectory control, the new method uses the product of force and velocity, namely, the power transmitted from the excavator to the soil, as a signal for adaptive excavation. Using an extremum-seeking algorithm, an optimal excavation condition where the force and velocity at the bucket take a particular combination that maximizes the output power of the machine is sought and maintained. Under this condition, the system finds the optimal depth of digging by controlling the boom of the excavator. Also under this condition, the output impedance of the excavator matches the impedance of the load and, thereby, transmits the maximum power from the machine to the soil. Theoretical analysis proves that an optimal combination of force and velocity exists and is unique under mild assumptions. An extremum-seeking algorithm using recursive least squares is developed for maximizing the output power. The method is implemented on a small-scale prototype system where torque motors emulate nonlinear force-speed characteristics of hydraulic actuators. Experiments demonstrate that the prototype can execute excavation tasks adaptively against varying soil properties and terrain profile.