'Mobile robots' presentation slideshows

Wireless Medium Access Control

Wireless Medium Access Control. Nitin Vaidya Department of Computer Science Texas A&M University vaidya@cs.tamu.edu. Acknowledgements. Joint work with Victor Bahl, Anurag Dugar, Seema Gupta, Young-Bae Ko. Outline. Introduction MAC protocols Fair scheduling MAC Directional MAC.

901 views • 69 slides

541 views • 54 slides

Linguistic Spatial Reasoning

573 views • 44 slides

http:// www.bbc.co.uk /news/technology-24427821

503 views • 41 slides

EEE 428 Introduction to Robotics

1.01k views • 37 slides

Emergent Task Allocation for Mobile Robots

Emergent Task Allocation for Mobile Robots Nuzhet Atay Doctoral Student Seminar Advisor : Burchan Bayazit Motivation Given an unknown environment and a swarm of mobile robots Achieve some goals under a set of constraints Explore the environment Regions of interest Dynamic Unpredictable

734 views • 36 slides

SLAM Using Single Laser Range Finder

SLAM Using Single Laser Range Finder. AliAkbar Aghamohammadi , Amir H. Tamjidi , Hamid D. Taghirad Advance Robotic and Automation Systems Lab (ARAS), Electrical and Computer Engineering Department K. N. Toosi University of Technology, Iran. Outline. 1-Motivation & Contributions

509 views • 35 slides

Part II: Platforms, Energy and OS

763 views • 34 slides

Mobile Emulab: A Robotic Wireless and Sensor Network Testbed

Mobile Emulab: A Robotic Wireless and Sensor Network Testbed D. Johnson, T. Stack, R. Fish, D.M. Flickinger, L. Stoller, R. Ricci, J. Lepreau School of Computing, University of Utah (Jointly with Department of Mech. Eng.) www.emulab.net IEEE Infocom, April 2006

1.25k views • 31 slides

Mobile Emulab: A Robotic Wireless and Sensor Network Testbed

Mobile Emulab: A Robotic Wireless and Sensor Network Testbed. D. Johnson, T. Stack, R. Fish, D.M. Flickinger, L. Stoller, R. Ricci, J. Lepreau School of Computing, University of Utah (Jointly with Department of Mech. Eng.) www.emulab.net IEEE Infocom, April 2006.

491 views • 31 slides

Reward Functions for Accelerated Learning

Reward Functions for Accelerated Learning. Presented by Alp Sarda?. Why RL?. RL a methodology of choice for learning in a variety of different domains. Convergence property. Potential biological relevance. RL is good in: Game playing Simulations. Cause of Failure.

379 views • 29 slides

At a glance

567 views • 27 slides

ROBOT

System Architecture for Human-Robot Interaction HUMAN ROBOT Robot Agent Human Agent A A A A A A A A IMA Primitive Agent Software System Hardware System Hardware Interface Human Interaction

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Sensors and Actuators

744 views • 23 slides

Dead Reckoning System for Mobile Robots

Dead Reckoning System for Mobile Robots. Lee Fithian Steven Parkinson Ajay Joseph Saba Rizvi. Dead Reckoning. Navigation Method used for Centuries Based on Measurements of Distance Traveled from a Known Point Used by Columbus to Discover the New World

486 views • 13 slides

Bill Piersol Robot Venture Program Manager bill.piersol@kcg-inc.net

510 views • 13 slides

RISCBOT: Mobile Robots Exploration And Mapping In 2D

268 views • 11 slides

Sonar and the Uses in Mobile Robots

370 views • 11 slides

Robotics History

Robotics History. What we will cover. Robot History Industrial Robotics Conventional Robotics and Failure Mobile Robots. Jacques de Vaucanson. Master toy maker who won the heart of Europe.

335 views • 6 slides

Emergent Task Allocation for Mobile Robots

449 views • 1 slides