SPLINE-BASED OPTIMAL TRAJECTORY GENERATION FOR AUTONOMOUS EXCAVATOR

Spline-Based Optimal Trajectory Generation for Autonomous Excavator

Spline-Based Optimal Trajectory Generation for Autonomous Excavator

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In this paper, we propose a novel trajectory generation method for Glasses 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 Solar Light 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.

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