Towards Autonomous Excavation Planning

TL;DR

This paper presents a fully autonomous excavation planning system that maps sites, plans sequences, and executes digging tasks, achieving efficiency comparable to human operators in large-scale excavation tasks.

Contribution

It introduces a novel integrated system for autonomous excavation planning, combining global, local, and digging planners for the first time.

Findings

Successfully excavated the largest pit documented so far.

Achieved an average digging cycle time of about 30 seconds.

Demonstrated potential for fully autonomous construction site operations.

Abstract

Excavation plans are crucial in construction projects, dictating the dirt disposal strategy and excavation sequence based on the final geometry and machinery available. While most construction processes rely heavily on coarse sequence planning and local execution planning driven by human expertise and intuition, fully automated planning tools are notably absent from the industry. This paper introduces a fully autonomous excavation planning system. Initially, the site is mapped, followed by user selection of the desired excavation geometry. The system then invokes a global planner to determine the sequence of poses for the excavator, ensuring complete site coverage. For each pose, a local excavation planner decides how to move the soil around the machine, and a digging planner subsequently dictates the sequence of digging trajectories to complete a patch. We showcased our system by autonomously excavating the largest pit documented so far, achieving an average digging cycle time of roughly 30 seconds, comparable to the one of a human operator.