Optimized Trajectory Planning and Kalman Filter-Enhanced INDI Motion Control for Spherical Robots

Engineering notes

By combining state estimation with incremental dynamic inversion, the controller achieves trajectory tracking without relying on precise dynamic models, accelerometers, or computationally intensive algorithms. For trajectory planning, a differential flatness-based approach is adopted to transform complex differential equation constraints into geometric optimization problems in the flat output space, significantly improving planning efficiency and providing real-time reference trajectories for the controller.

Chinese explanation / 中文解读

中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。

Original abstract

Spherical robots face significant challenges in precise modeling and motion control due to their nonlinear and strongly coupled dynamics. This paper proposes a novel motion controller that integrates Incremental Nonlinear Dynamic Inversion (INDI) with Kalman filtering. By combining state estimation with incremental dynamic inversion, the controller achieves trajectory tracking without relying on precise dynamic models, accelerometers, or computationally intensive algorithms. For trajectory planning, a differential flatness-based approach is adopted to transform complex differential equation constraints into geometric optimization problems in the flat output space, significantly improving planning efficiency and providing real-time reference trajectories for the controller. Physical experiments demonstrate that the proposed controller exhibits excellent real-time performance, and when combined with the improved trajectory planning method, enables autonomous motion of spherical robots in complex scenarios.

Links and sources

• Official / arXiv page

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