GIRA: Gaussian Mixture Models for Inference and Robot Autonomy

arXiv:2307.00071v3 Announce Type: cross
Abstract: This paper introduces the open-source framework, GIRA, which implements fundamental robotics algorithms for reconstruction, pose estimation, and occupancy modeling using compact generative models. Compactness enables perception in the large by ensuring that the perceptual models can be communicated through low-bandwidth channels during large-scale mobile robot deployments. The generative property enables perception in the small by providing high-resolution reconstruction capability. These properties address perception needs for diverse robotic applications, including multi-robot exploration and dexterous manipulation. State-of-the-art …

abstract algorithms arxiv autonomy bandwidth channels compact cs.cg cs.cv cs.lg cs.ro deployments framework generative generative models inference low mobile modeling paper perception robot robotics scale through type