Optimization-Based Framework for Excavation Trajectory Generation

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

2 Scopus Citations
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Detail(s)

Original languageEnglish
Article number9351610
Pages (from-to)1479-1486
Journal / PublicationIEEE Robotics and Automation Letters
Volume6
Issue number2
Online published9 Feb 2021
Publication statusPublished - Apr 2021

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.

Research Area(s)

  • Mining robotics, robotics in construction, trajectory optimization

Citation Format(s)

Optimization-Based Framework for Excavation Trajectory Generation. / Yang, Yajue; Long, Pinxin; Song, Xibin; Pan, Jia; Zhang, Liangjun.

In: IEEE Robotics and Automation Letters, Vol. 6, No. 2, 9351610, 04.2021, p. 1479-1486.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review