Now showing items 1-5 of 5
Industrial-Scale Autonomous Wheeled-Vehicle Path Following by Combining Iterative Learning Control with Feedback Linearization
Abstract— This paper presents a path following method for autonomous wheeled vehicles that combines iterative learning control (ILC) with nonlinear feedback linearization (FBL) to provide anticipatory control action ...
Towards Controlling Bucket Fill Factor in Robotic Excavation by Learning Admittance Control Setpoints
This paper investigates the extension of an admittance control scheme to- ward learning and adaptation of its setpoints to achieve controllable bucket fill factor for robotic excavation of fragmented rock. A previously ...
Admittance Control for Robotic Loading: Underground Field Trials with an LHD
In this paper we describe field trials of an admittance-based Autonomous Loading Controller (ALC) applied to a robotic Load-Haul-Dump (LHD) machine at an underground mine near Orebro, Sweden. The ALC was tuned and field ...
Iterative Learning-Based Admittance Control for Autonomous Excavation
(Springer Netherlands, 2019-02-07)
This paper presents the development and field validation of an iterative learning-based admittance control algorithm for autonomous excavation in fragmented rock using robotic wheel loaders. An admittance control strategy ...
Admittance Control for Robotic Loading: Design and Experiments with a 1-Tonne Loader and a 14-Tonne LHD
This paper describes the design, tuning, and extensive field testing of an admittance-based Autonomous Loading Controller (ALC) for robotic excavation. Several iterations of the ALC were tuned and tested in fragmented rock ...