Towards autonomous excavation in tough terrains and unobservable obstacles

Current autonomous excavation methods often make the assumption that the terrain within their environment is homogeneous, and remains free of obstacles. This assumption is insufficient for safe and reliable systems in the real world. Real autonomous excavation agents have to adapt to uncertainty within their environments such as changing terrain conditions and colliding with obstacles during an excavation fill cycle. In this work, we seek to improve autonomous excavation methods by introducing a novel set of scooping primitives to assist in breaking up jammed materials, a novel Reactive Attractor Impedance Controller (RAIC) that dampens trajectories when facing high impedances during the scooping cycle, and finally, we introducing a framework for material parameter estimation using tactile feedback. Our most novel methods comes in the form of our scooping primitives and our RAIC controller. These primitives are a set of oscillatory movement primitives with the intention of breaking up jammed particles encountered during the robot’s excavation cycle. Our RAIC controller works in tandem with our scooping primitives to help dampen and stop the robot’s end-effector trajectory when experiencing high forces to then break up the jammed materials. We evaluated these methods on a variety terrains and found them to vastly improve material scooped, as well as ensuring better safety over standard methods. Our material parameter estimation framework proposes using a simple force estimation method when dragging and intruding surface through granular media. This method, Resistive Force Theory (RFT), allows us to predict forces on our end-effector, while only requiring a single parameter ζ, the terrain’s resistivity coefficient. In addition to this RFT model, we propose a material deformation model based on the estimated forces to displace and settle the granular media between time steps. We then go on to explain how, in future works, this model can be used to estimate the local ζ to create a heterogeneous terrain property map to be used in excavation environments.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Electrical & Computer Engr

Grantor

University of Illinois Urbana-Champaign

Year dc:date

2025

Author dc:creator

• Franceschini, Noah E.

Contributors dc:contributor

• Hauser, Kris K.

• Robotics
• Controls

Statement dc:rights

• Copyright 2025 Noah Franceschini

Language dc:language

en, eng

Handle dc:identifier

https://hdl.handle.net/2142/129347

OAI record oai:identifier

https://www.ideals.illinois.edu/oai-pmh?verb=GetRecord&metadataPrefix=etdms&identifier=oai%3Awww.ideals.illinois.edu%3A2142%2F129347