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Advancements in Stochastic Estimation for Autonomous Robotics at Texas Tech University

Explore the innovative research conducted in the Stochastic Estimation and Autonomous Robotics Lab at Texas Tech University. This presentation discusses the significance of integrating systems that sense and interact with the real world, covering diverse applications from surveillance and elderly care to robotics in sports. Challenges include partial observability and limited human interaction. Our focus is on designing autonomous systems that learn, adapt, and effectively communicate, with implications beyond robotics, such as in online education and game development.

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Advancements in Stochastic Estimation for Autonomous Robotics at Texas Tech University

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  1. 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

  2. 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.

  3. 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.

  4. 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!

  5. Human View of Robot Soccer NSF REU 2012

  6. Robot’s view NSF REU 2012

  7. HRI is Easy – yeah, right  NSF REU 2012

  8. What about Teamwork? NSF REU 2012

  9. 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

  10. 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

  11. 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

  12. 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

  13. 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

  14. 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

  15. 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

  16. Robot Soccer Video NSF REU 2012

  17. Simulated Domains (Tetris, Robot Soccer) • Similar challenges but morestructured. • Multiagent collaboration. • Human-agent collaboration: learn from minimal human feedback. NSF REU 2012

  18. 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

  19. That’s all folks  • Any questions? NSF REU 2012

  20. That’s all folks  NSF REU 2012

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