4 accepted papers
Navigation Foundation Models (NFMs) trained on large, cross-embodied datasets have demonstrated powerful generalizability on various scenarios. Adopting in-domain fine-tuning upon an NFM efficiently calibrates the visuomotor policy, promising further improvement even in a novel scenario. However, th…
Monocular visual odometry is a key technology in various autonomous systems. Traditional feature-based methods suffer from failures due to poor lighting, insufficient texture, and large motions. In contrast, recent learning-based dense SLAM methods exploit iterative dense bundle adjustment to addres
We study how to generalize the visuomotor policy of a mobile manipulator from the perspective of visual observations. The mobile manipulator is prone to occlusion owing to its own body when only a single viewpoint is employed and a significant domain shift when deployed in diverse situations. Howeve…
Autonomous vehicles and robots need to operate over a wide variety of scenarios in order to complete tasks efficiently and safely. Multi-camera self-supervised monocular depth estimation from videos is a promising way to reason about the environment, as it generates metrically scaled geometric predi…