Sandra Hirche

Computationally Efficient Rigid-Body Gaussian Process for Motion Dynamics

2017 · IEEE Robotics and Automation Letters

In this letter, we address the modeling and learning of complex nonlinear rigid-body motions employing Gaussian processes. As the common procedure of using Euler angles in the Gaussian process results in inaccurate predictions for large …

Vision-Based Uncertainty-Aware Motion Planning based on Probabilistic Semantic Segmentation

2022 · arXiv (Cornell University)

For safe operation, a robot must be able to avoid collisions in uncertain environments. Existing approaches for motion planning under uncertainties often assume parametric obstacle representations and Gaussian uncertainty, which can be inaccurate. While visual …