Transformers have significantly impacted domains like natural language processing,
computer vision, and robotics, where they improve performance compared to other neural …

We propose a meta-ability decoupling (MAD) paradigm, which brings together various
object navigation methods in an architecture system, allowing them to mutually enhance …

Abstract" Search for" or" Navigate to"? When we find a specific object in an unknown
environment, the two choices always arise in our subconscious mind. Before we see the …

Object Goal Navigation (ObjectNav) aims at directing an agent to a specified target object
within an unseen scene. This task integrates advanced techniques, including visual …

Multimodal fusion of sensors is a commonly used approach to enhance the performance of
odometry estimation, which is also a fundamental module for mobile robots. Recently …

Robust obstacle avoidance is one of the critical steps for successful goal-driven indoor
navigation tasks. Due to the obstacle missing in the visual image and the possible missed …

Over the past few years, there has been a great deal of research on navigation tasks in
indoor environments using deep reinforcement learning agents. Most of these tasks use only …

This paper describes a domestic service robot (DSR) that fetches everyday objects and
carries them to specified destinations according to free-form natural language instructions …

The Embodied AI is the current frontier direction in the field of AI and is regarded as a
research leading to general artificial intelligence. Embodied AI refers to the study and …

This paper tackles the critical challenge of object navigation in autonomous navigation
systems, particularly focusing on the problem of target approach and episode termination in …