Person Following by Autonomous Robots: A Categorical Overview

TL;DR

This paper offers a comprehensive categorization and analysis of the diverse methods, challenges, and applications of person-following autonomous robots across different environments, highlighting current state-of-the-art techniques and future research directions.

Contribution

It provides a structured overview of person-following robotics, categorizing methods, discussing operational challenges, and comparing state-of-the-art approaches across various scenarios.

Findings

Different sensors and control strategies suit specific environments.

State-of-the-art perception and planning methods vary by scenario.

Open problems include robustness and adaptability in complex settings.

Abstract

A wide range of human-robot collaborative applications in diverse domains such as manufacturing, health care, the entertainment industry, and social interactions, require an autonomous robot to follow its human companion. Different working environments and applications pose diverse challenges by adding constraints on the choice of sensors, the degree of autonomy, and dynamics of a person-following robot. Researchers have addressed these challenges in many ways and contributed to the development of a large body of literature. This paper provides a comprehensive overview of the literature by categorizing different aspects of person-following by autonomous robots. Also, the corresponding operational challenges are identified based on various design choices for ground, underwater, and aerial scenarios. In addition, state-of-the-art methods for perception, planning, control, and interaction are elaborately discussed and their applicability in varied operational scenarios are presented. Then, some of the prominent methods are qualitatively compared, corresponding practicalities are illustrated, and their feasibility is analyzed for various use-cases. Furthermore, several prospective application areas are identified, and open problems are highlighted for future research.