Paper Info
Title
Proactive-Cooperative Navigation In Human-Like Environment For Autonomous Robots
Abstract
This work(1) deals with the problem of navigating a robot in a constrained human-like environment. We provide a method to generate a control strategy that enables the robot to proactively move in order to induce desired and socially acceptable cooperative behaviors in neighboring pedestrians. Contrary to other control strategies that simply aim to passively avoid neighboring pedestrians, this approach aims to simplify the navigation task of a robot by looking for cooperation with humans, especially in crowded and constrained environments. The co-navigation process between humans and a robot is formalized as a multi-objective optimization problem and a control strategy is obtained through the Model Predictive Control (MPC) approach. The Extended Headed Social Force Model with Collision Prediction (EHSFM with CP) is used to predict the human motion. Different social behaviors of humans when moving in a group are also taken into account. A switching strategy between purely reactive and proactive-cooperative planning depending on the evaluation of human intentions is also furnished. Validation of the proactive-cooperative planner enables the robot to generate more socially and understandable behaviors is done with different navigation scenarios.
Year
DOI
Venue
2020
10.5220/0009822004120419
ICINCO: PROCEEDINGS OF THE 17TH INTERNATIONAL CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS
Keywords
DocType
Citations 
Human-robot Interaction, Proactive Planning, Cooperative Behavior, Social Force Model
Conference
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Wanting Jin100.34
Paolo Salaris200.34
Philippe Martinet300.34