Real-Time Motion Planning of a Hydraulic Excavator using Trajectory Optimization and Model Predictive Control

Automation of excavation tasks requires real-time trajectory planning satisfying various constraints. To guarantee both constraint feasibility and real-time trajectory re-plannability, we present an integrated framework for real-time optimization-based trajectory planning of a hydraulic excavator. The proposed framework is composed of two main modules: a global planner and a real-time local planner. The global planner computes the entire global trajectory considering excavation volume and energy minimization while the local counterpart tracks the global trajectory in a receding horizon manner, satisfying dynamic feasibility, physical constraints, and disturbance-awareness. We validate the proposed planning algorithm in a simulation environment where two types of operations are conducted in the presence of emulated disturbance from hydraulic friction and soil-bucket interaction: shallow and deep excavation. The optimized global trajectories are obtained in an order of a second, which is tracked by the local planner at faster than 30 Hz. To the best of our knowledge, this work presents the first real-time motion planning framework that satisfies constraints of a hydraulic excavator, such as force/torque, power, cylinder displacement, and flow rate limits.

I. Introduction

Automation of heavy machinery, especially hydraulic excavators for its versatility, has been a steady research topic over a few decades. Various types of tasks, for example, soil digging [1], [2], rock moving [3], [4], and truck loading [5], are studied for excavator automation. To perform one of the most fundamental operation among such tasks, soil excavation, trajectory planning complying to operational constraints (e.g. swept volume constraint during digging or bucket tip pose constraint during grading) and physical constraints (e.g. actuator force/torque limit, pump flow rate limit, or power limit) is essential. To achieve such objective of planning a constrained reference trajectory, trajectory optimization has been widely applied [6]–[9]. However, since most existing works via trajectory optimization optimize the entire trajectory at once offline, they are vulnerable to instantaneous disturbance during operation. Furthermore, external disturbances to hydraulic excavators such as soil-bucket interaction and hydraulic friction are usually intractable and unignorable; accordingly, such unmodelable dynamics could result in sub-optimality and even constraint violation. Therefore, a new trajectory planning approach to consider constraints and compensate real-time disturbance is required.