4 papers · 1 filter
LMD-PGN: Cross-Modal Knowledge Distillation from First-Person-View Images to Third-Person-View BEV Maps for Universal Point Goal Navigation
Riku Uemura, Kanji Tanaka, Kenta Tsukahara +1
Point goal navigation (PGN) is a mapless navigation approach that trains robots to visually navigate to goal points without relying on pre-built maps. Despite significant progress…
ON as ALC: Active Loop Closing Object Goal Navigation
Daiki Iwata, Kanji Tanaka, Shoya Miyazaki +1
In simultaneous localization and mapping, active loop closing (ALC) is an active vision problem that aims to visually guide a robot to maximize the chances of revisiting previously…
CON: Continual Object Navigation via Data-Free Inter-Agent Knowledge Transfer in Unseen and Unfamiliar Places
Kouki Terashima, Daiki Iwata, Kanji Tanaka
This work explores the potential of brief inter-agent knowledge transfer (KT) to enhance the robotic object goal navigation (ON) in unseen and unfamiliar environments. Drawing on t…
Training Self-localization Models for Unseen Unfamiliar Places via Teacher-to-Student Data-Free Knowledge Transfer
Kenta Tsukahara, Kanji Tanaka, Daiki Iwata
A typical assumption in state-of-the-art self-localization models is that an annotated training dataset is available in the target workspace. However, this does not always hold whe…