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Found 7 papers, 2 papers with code
Can LLMs Generate Human-Like Wayfinding Instructions? Towards Platform-Agnostic Embodied Instruction Synthesis
We present a novel approach to automatically synthesize "wayfinding instructions" for an embodied robot agent.
Right Place, Right Time! Towards ObjectNav for Non-Stationary Goals
We address this concern by inferring results on two cases for object placement: one where the objects placed follow a routine or a path, and the other where they are placed at random.
Can an Embodied Agent Find Your "Cat-shaped Mug"? LLM-Guided Exploration for Zero-Shot Object Navigation
We present LGX (Language-guided Exploration), a novel algorithm for Language-Driven Zero-Shot Object Goal Navigation (L-ZSON), where an embodied agent navigates to a uniquely described target object in a previously unseen environment.
CLIP-Nav: Using CLIP for Zero-Shot Vision-and-Language Navigation
Our results on the coarse-grained instruction following task of REVERIE demonstrate the navigational capability of CLIP, surpassing the supervised baseline in terms of both success rate (SR) and success weighted by path length (SPL).
Can a Robot Trust You? A DRL-Based Approach to Trust-Driven Human-Guided Navigation
We utilize both these trust metrics into an optimal cognitive reasoning scheme that decides when and when not to trust the given guidance.
ProxEmo: Gait-based Emotion Learning and Multi-view Proxemic Fusion for Socially-Aware Robot Navigation
Our approach predicts the perceived emotions of a pedestrian from walking gaits, which is then used for emotion-guided navigation taking into account social and proxemic constraints.
Ranked #1 on
Emotion Classification
on EWALK
A Deep Learning Approach for Robust Corridor Following
For an autonomous corridor following task where the environment is continuously changing, several forms of environmental noise prevent an automated feature extraction procedure from performing reliably.
