Coordination for Multi-Robot Exploration and Mapping
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
A frontier-based approach for autonomous exploration
CIRA '97 Proceedings of the 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation
Visual Search and Dual Tasks Reveal Two Distinct Attentional Resources
Journal of Cognitive Neuroscience
Adaptive teams of autonomous aerial and ground robots for situational awareness: Field Reports
Journal of Field Robotics - Special Issue on Teamwork in Field Robotics
Little Ben: The Ben Franklin Racing Team's entry in the 2007 DARPA Urban Challenge
Journal of Field Robotics - Special Issue on the 2007 DARPA Urban Challenge, Part II
Motion planning in urban environments
Journal of Field Robotics
Robust and efficient robotic mapping
Robust and efficient robotic mapping
RGB-D mapping: Using Kinect-style depth cameras for dense 3D modeling of indoor environments
International Journal of Robotics Research
Exploration and mapping with autonomous robot teams
Communications of the ACM
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In this report, we describe the technical approach and algorithms that have been used by the University of Pennsylvania in the MAGIC 2010 competition. We have constructed and deployed a multi-vehicle robot team, consisting of intelligent sensor and disrupter unmanned ground vehicles that can survey, map, recognize, and respond to threats in a dynamic urban environment with minimal human guidance. The custom hardware systems consist of robust and complementary sensors, integrated electronics, computation, and highly capable propulsion and actuation. The mapping, navigation, and planning software is organized hierarchically, allowing autonomous decisions to be made by the robots while enabling human operators to interact with the robot team in an efficient and strategic manner. The ground control station integrates information coming from the robots as well as metadata feeds to focus the attention of the operators and respond rapidly to emerging threats. These systems were developed and tested by the UPenn team to complete two phases of the MAGIC 2010 challenge in a safe and timely manner. © 2012 Wiley Periodicals, Inc. © 2012 Wiley Periodicals, Inc.