Work

Optimal Control Meets Heavy Machinery: Trajectory Planning for Excavator Automation under complex geometric constraints

Year: 2026

Type: conference-paper

Abstract: This work presents an Optimal Control Problem (OCP) for Trajectory Optimization (TO) to generate smooth, statically and dynamically stable, time-efficient and collision-free motions of a mobile walking excavator boom for repetitive tasks, such as digging a trench or filling a truck. This work focuses on comparing two different approaches to handling self-collision constraints arising from the complex geometry of the excavator’s undercarriage. The systematic comparison showed that approximating the undercarriage geometry by a smooth Gaussian-RBF surface reduces the inequality-constraint count of the OCP by a factor of 22 and the IPOPT solver wall time by 3–5× compared to capsules and spheres, while preserving the optimized trajectory time and converging on all 56 tested start-goal pairs.

Source: IEEE/ASME International Conference on Advanced Intelligent Mechatronics

DOI: 10.1109/aim65483.2026.11658292

Authors: Robin Vetsch, Lucas Falch, Christoph Würsch, Sebastien Nicolas Gros

Institutions: Norwegian University of Science and Technology, OST - Ostschweizer Fachhochschule, University of Applied Sciences of Eastern Switzerland

Language: English

Topic: Robotic Path Planning Algorithms

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: hybrid

OpenAlex ID: W7204197855

FWCI:

Cites: 18

Cited by:

Related to: 10