Building of a Heterogeneous Segway Soccer Team towards a Peer-to-Peer Human Robot

Robotic soccer is an adversarial multi-agent research domain, in which issues of perception, multi-agent coordination and team strategy are explored. One area of interest investigates heterogeneous teams of humans and robots, where the teammates must coordinate not as master and slave, but as equal participants. We research this peer-to-peer question within the domain of Segway soccer, where teams of humans riding Segway HTs and robotic Segway RMPs coordinate together in competition against other human-robot teams. Beyond the task of physically enabling these robots to play soccer, a key issue in the development of such a heterogeneous team is determining the balance between human and robot player. The first ever Segway soccer competition occurred at the 2005 RoboCup US Open, where demonstrations were held between Carnegie Mellon University (CMU) and the Neurosciences Institute (NSI). Through the execution of these soccer demonstrations, many of the challenges associated with maintaining equality within a peer-to-peer game were revealed. This paper chronicles our experience within the Segway soccer demonstrations at the 2005 US Open, and imparts our interpretation and analysis regarding what is needed to better attain this goal of teammate equality within the peer-to-peer research domain. We begin with an explanation of the motivations behind the Segway soccer and peer-to-peer research, providing details of the game rules and flow. We then describe our approach to the building of a heterogeneous Segway soccer team, in which we developed a robot-dominated soccer strategy. Robot decision making was autonomous, and the human player reacted to the robot’s chosen actions. Our analysis of the experience at the US Open is presented, giving regard to both research challenges as well as difficulties in the physical execution of a Segway soccer game. We evaluate the strengths and weaknesses of our robot-driven approach within the context of game performance, as well as in contrast to the human-driven approach of our opponent team from NSI. While each team displayed either a strong bias towards the human or the robot, the intent of these peer-to-peer games is in fact teammate equality. We conclude with thoughts on the direction of future research within the Segway soccer domain. Copyright c © 2005, American Association for Artificial Intelligence (www.aaai.org). All rights reserved. Introduction There has been considerable research into both human-robot interaction (Nicolescu & Mataric 2003), and multi-agent teams (Dias & Stentz 2002). Additionally, since the inception of RoboCup robot soccer (Asada et al. 2003), there has been considerable research into robot teams operating in adversarial environments. To our knowledge, however, there has been no work yet that combines these attributes; namely, to examine human-robot interaction within an adversarial, multi-robot setting where humans and robots are team members with similar capabilities and no clear role hierarchy (Browning, Xu, & Veloso 2004; Searock, Browning, & Veloso 2004; Browning et al. 2004). Segway soccer is such a domain, where human and robot are teammates, both running on the Segway platform and thus uniform in physical capabilities. In such a human-robot team, how should we define the relationship between the human and the robot within a teammate framework? We can imagine two extremes in terms of the robot autonomy. One is a fully autonomous robot, without any interaction with the human player. The other is a tele-operated robot without any autonomy at all. Of course, neither extreme condition is desirable. Our intent in these peer-to-peer games is a truly equal relationship between teammates, where soccer plays are jointly devised and executed. A distinct effort must be made, therefore, to match human and robot capabilities, so that neither dominates the actions of the team or their teammate. From this equalization baseline then, true peer-topeer coordination may be investigated. The creation of this baseline most likely involves limiting the human player, as they are currently more capable at on-field decision making than their robotic teammate. Specifically within the realm of teammates advising one another, human teammates run the risk of giving advice so specific that the robot is essentially tele-operated by verbal commands. The first ever Segway soccer competition recently occurred at the 2005 RoboCup US Open, hosted by the Georgia Institute of Technology in Atlanta. The two participating teams were Carnegie Mellon University (CMU) and the Neurosciences Institute (NSI). During the game, CMU’s initial strategy was so focused in thrust on robot autonomy that it placed too little importance on the human player. The result was a lack of team performance, as the robot was in re-