CS393R: Autonomous Robots -- Resources

CS393R: Autonomous Robots -- Resources

Naos and UT Austin Villa

  • UT Austin Villa
  • Aldebaran Robotics
  • Aldebaran Nao H25 Datasheet
  • Codebase on GitHub
  • Lab/Robot Setup
  • Tutorial
  • Lab intro slides

  • Week 0: Class Overview

  • Slides from Thursday: (ppt).
  • RoboCup 2012 Final match (UT Austin Villa vs. B-Human)
  • RoboCup 2015 Final match (rUNSWift vs. B-Human)

  • Week 1: Vision basics

    Week 2: Introduction to motion control

  • Slides from Tuesday on control: (pdf, ppt).
  • A page with some control applets to play with. (applets may not work on all systems)
  • PID control on a quadrotor
  • Another tutorial on control by Thomas Dean and Michael Wellman.
  • Some videos on control
  • closed loop control
  • PID control - a brief introduction
  • Simple Examples of PID control
  • Effects of different gains for P, PI, PD, and PID
  • Some PID tuning heuristics
  • A Braitenberg simulator.
  • The whole Braitenberg book
  • A video of a Braitenberg vehicle #2
  • A video of the CMUnited team that used the Braitenberg love vehicle.

  • Week 3: Motion control continued

  • Slides on the joint modeling paper: (pdf).
  • I showed some slides (pdf) from lecture 2 of the 2008 class at CMU.
  • A paper that was based on a class project in the 2005 class that extended the joint modeling paper:
    A Neural Network-Based Approach to Robot Motion Control.
    Uli Grasemann, Daniel Stronger, and Peter Stone.
    In Ubbo Visser, Fernando Ribeiro, Takeshi Ohashi, and Frank Dellaert, editors, RoboCup-2007: Robot Soccer World Cup XI, Lecture Notes in Artificial Intelligence, pp. 480
  • Instance-Based Action Models for Fast Action Planning.
    Mazda Ahmadi and Peter Stone.
    In Ubbo Visser, Fernando Ribeiro, Takeshi Ohashi, and Frank Dellaert, editors, RoboCup-2007: Robot Soccer World Cup XI, Lecture Notes in Artificial Intelligence, pp. 1-16.
  • Creation of a Fine Controlled Action for a Robot.
    Ellie Lin, 2003

  • Week 4: Probability/Sensing

  • Some slides on sensors: (pdf). The ones I showed from CMU: (pdf).
  • Some additional slides on probability and Bayes' Rule (just the first 7 slides)
  • Slides from chapter 2 of the book: (ppt).
  • A Bayes' Theorem calculator and example.
  • Another.
  • Andrew Moore's tutorial on probability density functions, including variance/covariance.
  • A Udacity course that covers some of this material.
  • I showed some videos from Matt Mason's group on actions that reduce uncertainty

  • Week 5: Kalman Filters

  • Slides from Tuesday on Kalman filters: (ppt, pdf).
  • Slides from the book: (ppt, pdf).
  • wikipedia has a good 2D example.
  • More details from Welch and Bishop
  • A youtube tutorial endorsed by a student in the previous class.
  • Three other resources endorsed by students:
  • http://greg.czerniak.info/guides/kalman1/
  • https://www.udacity.com/wiki/cs373/kalman_filter_matrices
  • Kalman filter for dummies
  • A paper about the unscented Kalman Filter(UKF) and how it improves upon the EKF for estimation of non-linear systems (html version).
  • A RoboCup application of Kalman filters (see Section 2.3).
  • A description of the use of a Kalman Filter for ball tracking in RoboCup: Han and Veloso, 1997.
  • Newcastle RoboCup Team Report describing the Kalman Filter for localization and ball tracking. (See section 4). Quinlan et al, 2005.
  • CWMtx C++ Matrix library.

  • Week 6: Localization

    Additional readings:

    Week 7: Action and sensor models

  • Slides on ASAMI: (pdf)
  • Additional readings:

    Week 8: Path Planning

  • Slides from the intro lecture of Howie Choset's motion planning course. See also his slides on A*, D* lite, and sampling based methods.
  • Another presentation on D* lite.
  • UTSeaSim, which uses RRT for path planning. The slides.
  • Slides from Pieter Abbeel on motion planning that include information on PRMs and RRT*.
  • Urban challenge path planning paper:
    Practical Search Techniques in Path Planning for Autonomous Driving
  • Video of a holonomic robot
  • A* visualization
  • RRT page
  • An extension of RRT that interleaves execution
    Real-Time Randomized Path Planning for Robot Navigation
    James Bruce, Manuela Veloso
  • Karaman and Frazzoli introduce an algorithm that's asymptotically optimal called RRT*.
  • A paper on RRT with dynamic obstacles: Multipartite RRTs for Rapid Replanning in Dynamic Environments. Zucker et al.
  • A page on Voronoi planning
  • Sensor-Based Exploration: The Hierarchical Generalized Voronoi Graph
    Choset and Burdick
  • Voronoi page with applet
  • Three papers on the potential field approach: Borenstein, 1991; Konolige, 2000;
    Numerical Potential Field Techniques for Robot Path Planning: Barraquand, Langlois, Latombe
  • Craig Reynolds' boids (especially click on "steering")
  • Andrew Ng's A* search notes
  • Slides from Johns Hopkins and CMU on bug algorithms
  • Sven Koenig's site on LPA* and D* lite
  • Pieter Abbeel's paper on Environmentally Guided RRT's (a video of the talk is available from his homepage)

  • Week 9: Behavior Architectures

  • The planning slides (postscript).
  • A journal article with more details on the initial subsumption implementation:
    Brooks, R. A. "A Robust Layered Control System for a Mobile Robot", IEEE Journal of Robotics and Automation, Vol. 2, No. 1, March 1986, pp. 1423; also MIT AI Memo 864, September 1985. The detail slides from that article.
  • A radio interview with Rodney Brooks.
  • A journal article extending subsumption to multi-robot systems:
    Designing and Understanding Adaptive Group Behavior.
    Maja J Mataric.
    Adaptive Behavior 4:1, Dec 1995, 51-80.
  • Intelligence without Robots (A Reply to Brooks) by Oren Etzioni. AI Magazine, 14(4), December 1993.
  • Pengo
  • Experiences with an Architecture for Intelligent, Reactive Agents.
    R. Peter Bonasso, R. James Firby, Erann Gat, David Kortenkamp, David P. Miller, and Marc G. Slack.
    JETAI 9(2/3):237-256, 1997.
  • A paper on an architecture for action selection using value functions that was applied in simulated soccer. The accompanying slides.

  • Week 10: Walking

  • Slides on ZMP: (pdf)
  • Slides on the learned Aibo walk (starting at slide 57): (pdf)
  • Slides on the stable version: (pdf)
  • Slides on the skill optimization paper (starting at slide 78): (pdf)
  • Slides on transfer from simulation to real robots
  • Slides on bipedal robot control: (ppt)
  • Zero-Moment Point - Thirty Five Years of Its Life
    Vukobratovic, M. and Borovac, B.
    International Journal of Humanoid Robotics, Vol.1, No. 1, pp.157-173, 2004.
  • Biped Walking Pattern Generation by using Preview Control of Zero-Moment Point
    Kajita, S., Kanehiro, F., Kaneko, K., Fujiwara, K., Harada, K., Yokoi, K. and Hirukawa, H.
    ICRA 2003.
  • The Nao Devil's walking paper that uses ZMP and preview control
  • Observer based biped walking control, a sensor fusion approach
    Oliver Urbann and Stefan Tasse
    Autonomous Robots, July 2013
    The video of the evaluation for this paper
    a walking video from RoboCup 2015
  • Machine Learning for Fast Quadrupedal Locomotion
    Nate Kohl and Peter Stone
    In The Nineteenth National Conference on Artificial Intelligence, pp. 611-616, July 2004.
  • A paper on also optimizing for stability.
  • A paper on optimizing ball capturing.
  • A reference on Nelder-Mead (aka Amoeba). Another one.
  • A reference on Powell's method
  • On Optimizing Interdependent Skills: A Case Study in Simulated 3D Humanoid Robot Soccer
    Urieli, MacAlpine, Kalyanakrishnan, Bentor, and Stone
    AAMAS 2011
  • Videos from the omni-directional walk learning paper
  • A follow-up paper on transfering what was learned in simulation back to the real robots
  • Big dog in action. A paper about it.
  • A 2-legged follow-up to big dog, Petman
  • Their latest quadruped: Wildcat
  • ASIMO videos (check out the running one). Here's one where it walks up and down stairs. Here's some additional information on the walk.
  • Asimo playing soccer with Pres. Obama in 2014
  • A Nao climbing stairs
  • Kuka balancing robot
  • Luis Sentis' Human Centered Robotics Lab in the ME department here at UT does some cool research on biped locomotion.
  • RoboCup 2009 humanoid league videos.
  • RoboCup 2010 humanoid league videos.
  • Russ Tedrake's videos.
  • Chris Atkeson's course on Legged Locomotion
  • The development of Honda humanoid robot
    Hirai, K. and Hirose, M. and Haikawa, Y. and Takenaka, T.
    ICRA 1998.
  • Legged robots that balance.
    Raibert, M. H.
  • Virtual Model Control of a Bipedal Walking Robot
    Pratt, J., Dilworth, P. and Pratt, G.
    ICRA 1997.
  • Hybrid Zero Dynamics of Planar Biped Walkers
    Westervelt, E.R., Grizzle, J.W. and Koditschek, D.E.
    IEEE Trans. on Automatic Control, Vol.48, No.1, pp.42-56, 2003.
  • Modeling and Control of Multi-Contact Centers of Pressure and Internal Forces in Humanoid Robots
    Luis Sentis, Jaeheung Park, and Oussama Khatib.
    IROS 2009.
  • The 2014 rUNSWift team report gives an overview of their walk.
  • The 2010 rUNSWift team report has more details on their walk in Chapter 6.
  • Their 2011 Humanoids paper on using RL to control a biped's feet.

  • Week 11: Multi-Robot Coordination

  • Slides on ACLs and joint intentions: (pdf)
  • Slides on MAS and pursuit domain: (pdf)
  • Swarmanoid: a novel concept for the study of heterogeneous robotic swarms.
    Marco Dorigo et al.
    IEEE Robotics and Automation
  • Robot surveillance, Ahmadi and Stone, 2005.
  • Slides on continual area sweeping (pdf)
  • Videos of continual area sweeping.
  • Current Research in Multi-robot Systems.
    Lynne Parker
    ALife Robotics, 2003.
  • Theoretical Analysis of the Multi-agent Patrolling Problem.
    Yann Chevaleyre.
    IAT '04.
  • A fault-tolerant modular control approach to multi-robot perimeter patrol.
    Alessandro Marino, Lynne E. Parker, Gianluca Antonelli, Fabrizio Caccavale and Stefano Chiaverini.
    ROBIO '09.
  • Flexible Teamwork in Behavior-Based Robots.
    Gal A. Kaminka and Inna Frenkel.
    In Proceedings of the Twentieth National Conference on Artificial Intelligence (AAAI-05) , 2005.
  • A Realistic Model of Frequency-Based Multi-Robot Fence Patrolling.
    Yehuda Elmaliach, Asaf Shiloni, and Gal A. Kaminka.
    In Proceedings of the Seventh International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS-08)
    It's OK to skim sections 3.2 and 3.3. Make sure to understand what they analyze and how. It's OK not to follow the full details of the analysis (though it all should be accessible).
  • Follow-up and other interesting papers from Gal Kaminka's lab
  • Swarmanoid, winner of the 2011 AAAI video competition. And another video.
  • James McLurkin's work on multi-robot systems.
  • Collision avoidance with ClearPath and ORCA.
  • Video: Swarm robotics -- from local rules to global behaviors, Magnus Egerstedt, TEDxEmory
  • A video from his lab.
  • Kiva systems demo
  • Interview with Mick Mountz, Kiva CEO.
  • Kiva homepage.
  • Video about Kiva from a founder of the company.
  • Video about a Kiva robot.
  • Video of Kiva warehouse robots at work.
  • Video about Kiva robots at Zappos.
  • Video showing a teddy bear being shipped at Amazon using Kiva robots.
  • Video of Kiva dancing nut cracker robots.
  • Amazon Picking Challenge.
  • A recent TED talk by Raff D'andrea on his quadrotors research.
  • Trail-Laying Robots for Robust Terrain Coverage.
    J. Svennebring and S. Koenig.
    In Proceedings of the International Conference on Robotics and Automation (ICRA), 2003.
  • Sven Koenig's Ant Robotics page, including a video from the paper.
  • The Generation of Bidding Rules for Auction-Based Robot Coordination.
    C. Tovey, M. Lagoudakis, S. Jain and S. Koenig.
    In Multi-Robot Systems: From Swarms to Intelligent Automata, L. Parker, F. Schneider and A. Schultz (editor), 3-14. Springer, 2005.
  • Task Decomposition, Dynamic Role Assignment, and Low-Bandwidth Communication for Real-Time Strategic Teamwork.
    Stone and Veloso.
    AIJ, 1999.
    See sections 1-4, 6.1 and 7.1.
  • Slides on PTS domains, locker-room agreements (ps)
  • Slides on MAS in pursuit domains (ps)
  • A self-balancing table from Radhika Nagpal's lab.
  • self-configuring robots from USC.
  • On Team Formation.
    Cohen, P. R., Levesque, H. R., and Smith, I.
    in Hintikka, J. and Tuomela, R. (Eds.) Contemporary Action Theory. Synthese, 1997.
  • Ad Hoc Teamwork for Leading a Flock.
    Katie Genter, Noa Agmon, and Peter Stone.
    In Proceedings of the 12th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2013), May 2013.

  • Week 12: Applications

  • Kurt Dresner's slides on AIM. (keynote version)
  • More recent AIM slides
  • JoFR 2008 Special Issue on the 2007 DARPA Urban Challenge, Part I
  • JoFR 2008 Special Issue on the 2007 DARPA Urban Challenge, Part II
  • JoFR 2008 Special Issue on the 2007 DARPA Urban Challenge, Part III
  • Festo flying/swimming robots
  • A very fast robot hand
  • Anytime D*
  • Applications papers and related resources from a previous version of this course
  • Cloth Grasp Point Detection based on Multiple-View Geometric Cues with Application to Robotic Towel Folding.
    Jeremy Maitin-Shepard, Marco Cusumano-Towner, Jinna Lei and Pieter Abbeel.
    In the proceedings of the International Conference on Robotics and Automation (ICRA), 2010.
  • Autonomous helicopter control, Ng et al., 2004.
  • PEGASUS: A policy search method for large MDPs and POMDPs, Andrew Y. Ng and Michael Jordan. In Uncertainty in Artificial Intelligence, Proceedings of the Sixteenth Conference, 2000.
  • Andrew Ng's robot videos.
  • Robot air hockey, Bentivegna and Atkeson, 2002.
  • A paper about the Nursebot project.

  • Week 13: Social Implications

  • Bill Joy's TED talk from 2006.
  • Illah Nourbakhsh's course on ethics and robotics
  • Ron Arkin's tech report on embedding ethics in robots.
  • Some writings on the singularity: a resesarch institute, and Ray Kurzweil's page.
  • Jordan Pollack's GOLEM project: evolving physical robots.
  • Daniel Wilson's Robot Uprising book.
  • The Lifeboat Foundation is dedicated to assessing and protecting against threats to humanity.
  • Stephen Goose on The Case for Banning Killer Robots: Point in CACM, Dec. 2015.
  • Ron Arkin on The Case for Banning Killer Robots: Counterpoint in CACM, Dec. 2015.

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