RA-L 202152 citations

Optimization-Based Framework for Excavation Trajectory Generation

Yajue Yang, Pinxin Long, Xibin Song, Jia Pan, Liangjun Zhang

Abstract

In thisletter, we present a novel optimization-based framework for autonomous excavator trajectory generation under task-specific constraints. Traditional excavation trajectory generators over-simplify the geometric trajectory parameterization thereby limiting the space for optimization. To expand the search space, we formulate a generic task specification for excavation by constraining the instantaneous motion of the bucket and adding a target-oriented constraint to control the amount of excavated soil. The trajectory is represented with a waypoint interpolating spline. Time intervals between waypoints are relaxed as variables to facilitate generating the time-optimal trajectory in one stage. Experiments on a real robot platform demonstrate that our method is adaptive to different terrain shapes and outperforms other optimal path planners in terms of the minimum joint length and minimum travel time.

BibTeX
@inproceedings{ral2021_optimizationbase,
  title = {Optimization-Based Framework for Excavation Trajectory Generation},
  author = {Yajue Yang and Pinxin Long and Xibin Song and Jia Pan and Liangjun Zhang},
  booktitle = {RA-L 2021},
  year = {2021}
}
Optimization-Based Framework for Excavation Trajectory Generation · RA-L 2021