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• W4283798755 abstract "In this paper, we propose a novel trajectory generation method for autonomous excavator teach-and-plan applications. Rather than controlling the excavator to precisely follow the teaching path, the proposed method transforms the arbitrary slow and jerky trajectory of human excavation into a topologically equivalent path that is guaranteed to be fast, smooth and dynamically feasible. This method optimizes trajectories in both time and jerk aspects. A spline is used to connect these waypoints, which are topologically equivalent to the human teaching path. Then the trajectory is reparametrized to obtain the minimum time-jerk trajectory with the kinodynamic constraints. The optimal time-jerk trajectory generation method is both formulated using nonlinear programming and conducted iteratively. The framework proposed in this paper was integrated into a complete autonomous excavation platform and was validated to achieve aggressive excavation in a field environment." @default.
• W4283798755 created "2022-07-05" @default.
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• W4283798755 date "2022-07-03" @default.
• W4283798755 modified "2023-10-14" @default.
• W4283798755 title "Spline-Based Optimal Trajectory Generation for Autonomous Excavator" @default.
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• W4283798755 doi "https://doi.org/10.3390/machines10070538" @default.
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