Time Variable Minimum Torque Trajectory Optimization for Autonomous Excavator
Authors:
Preprint
Abstract
In this paper, we present a minimal torque and time variable trajectory optimization method for autonomous excavator considering the soil-tool interaction. The method formulates the excavation motion generation as a trajectory optimization problem and takes into account geometric, kinematic and dynamics constraints. To generate time-efficient trajectory and improve the overall optimization efficiency, we propose a time variable trajectory optimization mechanism so that the time intervals between the keypoints along the trajectory subject to the optimization. As a result, the method uses few keypoints and reduces the total number of optimization variables. We further introduce a soil-tool interaction force model, which considers the geometric shape of the bucket and the physical properties of the soil. The experimental result on a high fidelity dynamic simulator shows our method can generate feasible trajectories, which satisfy excavation task constraints and are adaptive to different soil conditions.Keywords
All Related Versions
This publication has 9 references indexed in Scilit:
- Archimedes’ law explains penetration of solids into granular mediaNature Communications, 2018
- Planning and Control for Autonomous ExcavationIEEE Robotics and Automation Letters, 2017
- Parallel Dynamics Computation Using Prefix Sum OperationsIEEE Robotics and Automation Letters, 2017
- Asymptotically optimal sampling-based kinodynamic planningThe International Journal of Robotics Research, 2016
- Motion planning with sequential convex optimization and convex collision checkingThe International Journal of Robotics Research, 2014
- Dynamically optimal trajectories for earthmoving excavatorsAutomation in Construction, 2013
- Dynamic modeling of soil–tool interaction: An overview from a fluid flow perspectiveJournal of Terramechanics, 2006
- Task Planning For Robotic Excavation2005
- Newton-type algorithms for dynamics-based robot movement optimizationIEEE Transactions on Robotics, 2005