Welcome to the homepage of TRaVERSE.
TRaVERSE: Towards Very Large Scale Human-Robot Synergy was a Marie Skłodowska-Curie Intra European Fellowship (MC-IEF) Project funded by the European Union (EU) through the FP7 People Programme.
Researcher: Dr. Aamir Ahmad
Scientist-in-Charge: Prof. Dr. Heinrich H. Bülthoff
Host Department: Human Perception, Cognition and Action
Host Institute: Max Planck Institute for Biological Cybernetics, Tübingen, Germany
Duration: September 2014 – August 2016
Scientific Abstract
Hazardous work environment for humans, growing necessity for an increase in the worldwide agricultural production, and a rapid rise in the public healthcare expenditures due to aging population are among some of the most predominant societal issues where robotics and automation are becoming progressively vital. Distributed multi-robot teams consisting of a large number of robots operating in close cooperation with humans is fundamental for such applications. How to achieve maximum synergy between teams of robots and humans, without jeopardizing human safety and comfort, within the constraints of resources, e.g., computational capacity of the robots, sensor and actuator costs, is still an open question. The focus of this research project is on investigating and developing integrated methods for robot team functionalities with human interaction that are scalable to a very large number of robots, thus enabling their successful real-world deployment. Using state of the art, ecologically valid and immersive virtual environments and virtual reality equipments, the project will study and model human behavior, perception and cognitive responses when they interact and/or cooperate with robots in a large-scale multi-robot scenario. Clear distinction will be made between human users and operators where the former is expected to benefit from directly using a robot that functions as a part of a large robotic team. On the other hand, human operators are those that are in charge of cooperating/controlling a team of robots to accomplish a collaborative task. Eventually, using the human behavior models, cooperative multi-robot functionalities, including localization, mapping and motion planning, will be optimally designed to be extremely scalable within the constraints of ease, safety, effectiveness and naturalness of human user/operator interaction with the robots.
