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Mohan Sridharan Stochastic Estimation and Autonomous Robotics Lab Department of Computer Science, Texas Tech University mohan.sridharan@ttu.edu. Robotics Overview and Research Projects. Motivation: why do we care?. Integrated systems: Sense and interact with the real-world.
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Mohan Sridharan Stochastic Estimation and Autonomous Robotics Lab Department of Computer Science, Texas Tech University mohan.sridharan@ttu.edu Robotics Overview and Research Projects NSF REU 2012
Motivation: why do we care? NSF REU 2012 • Integrated systems: • Sense and interact with the real-world. • Lots of applications: • Surveillance, personalized elderly care, robot soccer! • Algorithms applicable to non-robotics applications: • Game development, online education systems, security.
Challenges NSF REU 2012 • Partial observability: • Limited field of view, and varying degrees of uncertainty. • Difficult to operate without any human input! • Constrained processing: • Multiple sensors (and teammates) provide large amounts of raw data. • Limited human attention: • Humans do not have time and expertise to provide elaborate and accurate feedback. • Limited high-level feedback from non-experts.
Desiderata NSF REU 2012 Real-world (robot) systems require high reliability. Dynamic response requires real-time operation. Learn from limited feedback and operate autonomously. Much more than industrial automation!
Human View of Robot Soccer NSF REU 2012
Robot’s view NSF REU 2012
HRI is Easy – yeah, right NSF REU 2012
What about Teamwork? NSF REU 2012
Associated Skills • Prerequisite:lots of patience!! • Mathematics: calculus, trigonometry, probability. • Teamwork: often need expertise from different disciplines. • Programming: object-oriented, multi-threaded, Linux. NSF REU 2012
Research Focus • It is not all about robots! • Autonomous systems: • Systems that learn automatically and adapt to changes. • Stochastic estimation: • Model uncertainty in real-world systems. • Predict system behavior based on the learned models. • Some examples in a few slides. NSF REU 2012
High-level Questions • Can we design (autonomous) systems that: • Learn and adapt based on sensory inputs? • Plan actions appropriate for desired task(s)? • Interact with other systems and (non-expert) humans? NSF REU 2012
Human-Robot/Multirobot Teamwork • Examples: surveillance, disaster rescue, socially engage elderly. • Core skills: plan action sequence, visual processing, speech processing. • Basic tasks: localize targets, local obstacle avoidance, etc. NSF REU 2012
Indoor HRI: Challenges • Autonomously learn and revise models of objects/events. • Detect and adapt to unforeseen changes. • Represent knowledge, plan appropriate sequence of actions. • Limited high-level interaction with humans when required. NSF REU 2012
Robot Soccer • Create humanoid team to beat human soccer team by 2050. • Currently games played on indoor soccer fields. • Different leagues focus on hardware and software. NSF REU 2012
Robot Soccer: Challenges • Autonomous and real-time operation: • Learn and adapt to unforeseen changes. • Fuse information from different sensors. • Cameras, range finders, microphones, touch sensors etc. • Collaborate with teammates towards shared objective: win the game! NSF REU 2012
Robot Soccer Video NSF REU 2012
Simulated Domains (Tetris, Robot Soccer) • Similar challenges but morestructured. • Multiagent collaboration. • Human-agent collaboration: learn from minimal human feedback. NSF REU 2012
Educational Tools • Integrate 3D programming environments with autonomous robots. • Create graphical routines in Alice, automatically translated to code for autonomous behavior on one of more robots. • Teach core computing concepts (problem solving, abstraction) to school students (more details tomorrow afternoon). NSF REU 2012
That’s all folks • Any questions? NSF REU 2012
That’s all folks NSF REU 2012