Multi-Contact Inertial Estimation and Localization in Legged Robots
<|reference_start|>Multi-Contact Inertial Estimation and Localization in Legged Robots: Optimal estimation is a promising tool for multi-contact inertial estimation and localization. To harness its advantages in robotics, it is crucial to solve these large and challenging optimization problems efficiently. To tackle this, we (i) develop a multiple-shooting solver that exploits both temporal and parametric structures through a parametrized Riccati recursion. Additionally, we (ii) propose an inertial local manifold that ensures its full physical consistency. It also enhances convergence compared to the singularity-free log-Cholesky approach. To handle its singularities, we (iii) introduce a nullspace approach in our optimal estimation solver. We (iv) finally develop the analytical derivatives of contact dynamics for both inertial parametrizations. Our framework can successfully solve estimation problems for complex maneuvers such as brachiation in humanoids. We demonstrate its numerical capabilities across various robotics tasks and its benefits in experimental trials with the Go1 robot.<|reference_end|>
@article{martinez2024multi-contact,
    title={Multi-Contact Inertial Estimation and Localization in Legged Robots},
    author={Sergi Martinez, Robert Griffin, Carlos Mastalli},
    journal={arXiv preprint arXiv:2403.17161},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.17161},
    primaryClass={cs.RO}
}