User preferred behaviors for robot navigation exploiting previous experiences

• Published in: Robotics and autonomous systems 2017-11, Vol.97, p.204-216
• Main Authors: Nardi, Lorenzo, Stachniss, Cyrill
• Format: Article
• Language: English
• Subjects: Collision avoidance; Navigation; Path planning; Trajectory prediction
• ISSN: 0921-8890; 1872-793X
• DOI: 10.1016/j.robot.2017.08.014

Industry demands flexible robots that are able to accomplish different tasks at different locations such as navigation and mobile manipulation. Operators often require mobile robots operating on factory floors to follow definite and predictable behaviors. This becomes particularly important when a robot shares the workspace with other moving entities. In this paper, we present a system for robot navigation that exploits previous experiences to generate predictable behaviors that meet user’s preferences. Preferences are not explicitly formulated but implicitly extracted from robot experiences and automatically considered to plan paths for the successive tasks without requiring experts to hard-code rules or strategies. Our system aims at accomplishing navigation behaviors that follow user’s preferences also to avoid dynamic obstacles. We achieve this by considering a probabilistic approach for modeling uncertain trajectories of the moving entities that share the workspace with the robot. We implemented and thoroughly tested our system both in simulation and on a real mobile robot. The extensive experiments presented in this paper demonstrate that our approach allows a robot for successfully navigating while performing predictable behaviors and meeting user’s preferences. •Novel robot navigation system, that considers user preferences.•Preferences are collected from previous navigation experiences or demonstrations.•The experiences guide the planning process for generating predictable paths.•Probabilistic approach that predicts the motion of dynamic objects.•Planning system reproduces and generalizes behaviors for avoiding obstacles.