Environment Modeling for Service Robots From a Task Execution Perspective

TL;DR

This paper surveys environment modeling techniques for service robots in home settings, focusing on how these models support task execution, localization, navigation, manipulation, and long-term autonomy.

Contribution

It introduces a comprehensive review of environment modeling from a task-execution perspective, emphasizing recent advances and future research directions in domestic service robots.

Findings

Progress in environment perception and understanding for task execution.

Identification of key challenges in long-term autonomy and environment representation.

Highlighting research gaps and opportunities in environment modeling for service robots.

Abstract

Service robots are increasingly entering the home to provide domestic tasks for residents. However, when working in an open, dynamic, and unstructured home environment, service robots still face challenges such as low intelligence for task execution and poor long-term autonomy (LTA), which has limited their deployment. As the basis of robotic task execution, environment modeling has attracted significant attention. This integrates core technologies such as environment perception, understanding, and representation to accurately recognize environmental information. This paper presents a comprehensive survey of environmental modeling from a new task-executionoriented perspective. In particular, guided by the requirements of robots in performing domestic service tasks in the home environment, we systematically review the progress that has been made in task-execution-oriented environmental modeling in four respects: 1) localization, 2) navigation, 3) manipulation, and 4) LTA. Current challenges are discussed, and potential research opportunities are also highlighted.