16 citations · 24 across the 12 of their papers we have counts for
5 papers · 1 filter
A scalar per patch from pre-trained ViTs enables fast moving navigation in the real world
Steeven Janny, Leonid Antsfeld, Christian Wolf
Trained policies for real-world robotics rely on computer vision components, typically in the form of pre-trained visual encoders. These encoders are an essential component and it…
Reasoning in visual navigation of end-to-end trained agents: a dynamical systems approach
Steeven Janny, Hervé Poirier, Leonid Antsfeld +6
Progress in Embodied AI has made it possible for end-to-end-trained agents to navigate in photo-realistic environments with high-level reasoning and zero-shot or language-condition…
Learning to navigate efficiently and precisely in real environments
Guillaume Bono, Hervé Poirier, Leonid Antsfeld +3
In the context of autonomous navigation of terrestrial robots, the creation of realistic models for agent dynamics and sensing is a widespread habit in the robotics literature and…
Learning with a Mole: Transferable latent spatial representations for navigation without reconstruction
Guillaume Bono, Leonid Antsfeld, Assem Sadek +2
Agents navigating in 3D environments require some form of memory, which should hold a compact and actionable representation of the history of observations useful for decision takin…
Magnetic Field Sensing for Pedestrian and Robot Indoor Positioning
Leonid Antsfeld, Boris Chidlovskii
In this paper we address the problem of indoor localization using magnetic field data in two setups, when data is collected by (i) human-held mobile phone and (ii) by localization…