Anticipating Human Behavior for Safe Navigation and Efficient Collaborative Manipulation with Mobile Service Robots

TL;DR

This paper presents methods for robots to predict human movement and intentions using sensor networks, enhancing safety and efficiency in navigation and collaborative tasks like furniture arrangement.

Contribution

It introduces a novel approach to anticipate human behavior using sensor data for safe navigation and collaborative manipulation in mobile robots.

Findings

Anticipating human behavior improves navigation safety.

Predicting human intentions enhances collaborative efficiency.

Integrated system successfully collaborates with humans to arrange furniture.

Abstract

The anticipation of human behavior is a crucial capability for robots to interact with humans safely and efficiently. We employ a smart edge sensor network to provide global observations, future predictions, and goal information to integrate anticipatory behavior for the control of a mobile manipulation robot. We present approaches to anticipate human behavior in the context of safe navigation and collaborative mobile manipulation. First, we anticipate human motion by employing projections of predicted human trajectories from smart edge sensor observations into the planning map of a mobile robot. Second, we anticipate human intentions in a collaborative furniture-carrying task to achieve a given room layout. Our experiments indicate that anticipating human behavior allows for safer navigation and more efficient collaboration. Finally, we showcase an integrated robotic system that anticipates human behavior while collaborating with an operator to achieve a target room layout, including the placement of tables and chairs.