Robot Simulation on Agri-Field Point Cloud With Centimeter Resolution

The need for robotic agricultural automation has been driven by global population growth and climate change.To efficiently evaluate and develop agricultural robots not limited to the growing season, we developed a dynamics simulator that works fast on 3D point-cloud models of agricultural fields.The point-cloud models have been widely used in recent agricultural research thanks to advances in aerial photography technology. Therefore, the simulator can be easily applied to many agricultural fields.To speed up the dynamics calculation on the dense point-cloud model, we developed a method to quickly detect collision points using a grid table, and a method to calculate collision forces between the points and robot meshes.The performance of the simulator was evaluated on an agri-field model (<inline-formula> <tex-math notation="LaTeX">$31 \times 14$ </tex-math></inline-formula> m2) represented by <inline-formula> <tex-math notation="LaTeX">$1.7 \times 10^{6}$ </tex-math></inline-formula> points. The computation time of the simulation was 8.8 times faster than real time, and the simulation accuracy compared to actual robot movements was ~1 cm in Root Mean Square Error (RMSE). The simulator in this study enables fast computation and accurate prediction of robot movements on centimeter-resolution agri-field point-cloud models, supporting research on agricultural robots not limited to the growing season.