Artificial Intelligence Review - Special issue on lazy learning
CMPack: a complete software system for autonomous legged soccer robots
Proceedings of the fifth international conference on Autonomous agents
An Behavior-based Robotics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Natural methods for robot task learning: instructive demonstrations, generalization and practice
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
ÜberSim: a multi-robot simulator for robot soccer
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
An overview of RoboCup-2002 Fukuoka/Busan
AI Magazine
Constructive Incremental Learning from Only Local Information
Neural Computation
Effective team-driven multi-model motion tracking
Proceedings of the 1st ACM SIGCHI/SIGART conference on Human-robot interaction
Effective Multi-Model Motion Tracking using Action Models
International Journal of Robotics Research
A survey of robot learning from demonstration
Robotics and Autonomous Systems
Tactic-based motion modeling and multi-sensor tracking
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 3
Interactive policy learning through confidence-based autonomy
Journal of Artificial Intelligence Research
Learning from demonstration in robots: Experimental comparison of neural architectures
Robotics and Computer-Integrated Manufacturing
Evaluating the effects of limited perception on interactive decisions in mixed robotic domains
Proceedings of the 8th ACM/IEEE international conference on Human-robot interaction
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Dynamically-balancing robots have recently been made available by Segway LLC, in the form of the Segway RMP (Robot Mobility Platform). We have addressed the challenge of using these RMP robots to play soccer, building up upon our extensive previous work in this multi-robot research domain. In this paper, we make three contributions. First, we present a new domain, called Segway Soccer, for investigating the coordination of dynamically formed, mixed human-robot teams within the realm of a team task that requires real-time decision making and response. Segway Soccer is a game of soccer between two teams consisting of both Segway riding humans and Segway RMPs. We believe Segway Soccer is the first game involving both humans and robots in cooperative roles and with similar capabilities. In conjunction with this new domain, we present our work towards developing a soccer playing robot using the RMP platform with vision as its primary sensor. Our third contribution is that of skill acquisition from a human teacher, where the learned skill is then used seamlessly during robot execution as part of its control hierarchy. Skill acquisition and use addresses the challenge or rapidly developing the low-level actions that are environment dependent and are not transferable across robots.