Global Control for Robotic Excavation Using Fuzzy Logic and Statecharts

Abstract

This paper presents global strategies for the computer control of autonomous backhoe-type excavators. The control structure is divided into low and high levels. The low level control utilises fuzzy logic to encapsulate expert experience for capturing soil in many excavation scenarios. UML statecharts are used at the higher level for mapping environment and machine sensor data to actuator control signals. This mapping is based on a deep understanding of excavation performed by a skilful operator and is coded into rule sets. Transition between states or behaviours is accomplished via associated task characteristic functions that not only switch among tasks but also enable/disable rules according to digging phases. Typical excavation tasks are decomposed into statecharts and task elements. The control schemes are illustrated by autonomous trench digging. Field test results are provided to verify the validity of the proposed control architecture.