Optimization-Based Framework for Excavation Trajectory Generation

被引:38
|
作者
Yang, Yajue [1 ,2 ]
Long, Pinxin [2 ]
Song, Xibin [2 ]
Pan, Jia [3 ]
Zhang, Liangjun [2 ]
机构
[1] City Univ Hong Kong, Dept Biomed Engn, Hong Kong, Peoples R China
[2] Baidu Inc, Baidu Res, Beijing, Peoples R China
[3] Univ Hong Kong, Dept Comp Sci, Hong Kong, Peoples R China
来源
IEEE ROBOTICS AND AUTOMATION LETTERS | 2021年 / 6卷 / 02期
关键词
Mining robotics; robotics in construction; trajectory optimization;
D O I
10.1109/LRA.2021.3058071
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
In this letter, 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.
引用
收藏
页码:1479 / 1486
页数:8
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