5 papers
MOON: Multi-Objective Optimization-Driven Object-Goal Navigation Using a Variable-Horizon Set-Orienteering Planner
Daigo Nakajima, Kanji Tanaka, Daiki Iwata +1
This paper proposes MOON (Multi-Objective Optimization-driven Object-goal Navigation), a novel framework designed for efficient navigation in large-scale, complex indoor environmen…
LGR: LLM-Guided Ranking of Frontiers for Object Goal Navigation
Mitsuaki Uno, Kanji Tanaka, Daiki Iwata +3
Object Goal Navigation (OGN) is a fundamental task for robots and AI, with key applications such as mobile robot image databases (MRID). In particular, mapless OGN is essential in…
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…
Active Robot Vision for Distant Object Change Detection: A Lightweight Training Simulator Inspired by Multi-Armed Bandits
Kouki Terashima, Kanji Tanaka, Ryogo Yamamoto +1
In ground-view object change detection, the recently emerging mapless navigation has great potential to navigate a robot to objects distantly detected (e.g., books, cups, clothes)…