Overview
The field of robotics has been undergoing a major change from manufacturing applications to entertainment, home, rehabilitation, search and rescue, and service applications. Although robots seem to possess fantastic skills in science fiction and movies, most people would be surprised to learn how much remains to be accomplished to provide today's robots with the ability to do relatively simple tasks. Autonomous robots are only able to complete very simple tasks within limited environmental conditions. Humans can be incorporated to teleoperate or supervise robots, but as the robot complexity increases so does the human's workload. Robotics requires research in many areas that include hybrid systems, embedded systems, sensory fusion, distributed artificial intelligence, computer vision, machine learning, human-machine interaction, localization, planning, navigation, etc. This large field provides ample research problems.
The Engineering School's Department of Electrical Engineering and Computer Science houses the Center for Intelligent Systems (CIS) that encompasses both the Cognitive Robotics Lab (CRL) and the Intelligent Robotics Lab (IRL). In addition to CIS, the department also includes six addition laboratories that conduct robotics research: the Computational Cognitive Neuroscience Laboratory (CCN), the Embedded Computing Systems Laboratory (ECS), the Embedded and Hybrid Systems Laboratory (EHS), the Human-Machine Teaming Laboratory (HMT), the Modeling and Analysis of Complex Systems (MACS) group, and the Robotics and Autonomous Systems Laboratory (RAS). Each individual laboratory provides a specific robotics research focus. The broad research areas include: biologically inspired robotic control (CCNL), cognitive robotics (CRL),
embedded systems (ECS, EHS), human-robotic interaction (HMT, IRL, RAS), humanoid robotics (CRL), planning (MACS), sensor networks (EHS),
hybrid robotic systems (EHS, MACS), mobile robot navigation (IRL), multiple robot coordination and cooperation (HMT), real-time systems (EHS), and rehabilitation robotics (RAS).
Topics
Biologically inspired robot control
Decision-Theoretic planning and control
Humanoid robots
Human-robot interaction
Hybrid and Distributed Control
Knowledge sharing among robots
Mobile robot navigation
Mobile sensor networks
Modeling, simulation and diagnosis
Multiple robot coordination and cooperation
Personal and service robots
Range-free perception-based navigation
Rehabilitation robotics
Sensory EgoSphere
Stochastic hybrid systems for multiple robot teams
Vision, image and signal processing systems
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