Social Robotics Research Publications

Our publications demonstrate our transdisciplinary contributions have been made in a wide range of areas including human-robot interaction, social robotics, social intelligence, robot navigation, cognitive science, people tracking, belief revision, commonsense reasoning, case-based reasoning for robots, robot decision making, robot autonomoy, facial recognition, social interaction strategies, robot learning by human demonstration, autonomous vehicles, robot law.

Examples

  1. Siddharth and Mary-Anne Williams, (2017). Robot Authority and Human Obedience: A Study of Human Behaviour using a Robot Security Guard, Twelth ACM/IEEE International Conference on Human Robot Interation. IEEE Press.
  2. Syed Ali Raza and Mary-Anne Williams (2017). Potential Based Reward Shaping Using Learning to Rank, Twelth ACM/IEEE International Conference on Human Robot Interation. IEEE Press.
  3. Syed Ali Raza and Mary-Anne Williams (2017). Unconventional Formats of Background Knowledge from a Human Teacher in Reward Shaping, Twelth ACM/IEEE International Conference on Human Robot Interation HRI PIONEERS 2017 Workshop. IEEE Press.
  4. Hugo Romat, Mary-Anne Williams, Xun Wang, Benjamin Johnston, Henry Bard, (2016) Natural Human-Robot Interaction Using Social Cues, Eleventh ACM/IEEE International Conference on Human Robot Interation. IEEE Press, Pages: 503-504.
  5. Surden, H. and Williams, M-A., (2016) Technological Opacity, Predictability, and Self-Driving Cars, Cardozo Law Review, Volume 38 Number 1, 121 - 182.
  6. Vitale, J., Williams, M. A., & Johnston, B. (2016). The face-space duality hypothesis: a computational model. 38th Annual Meeting of the Cognitive Science Society.
  7. Williams, M-A. (2016) Decision-Theoretic Human-Robot Interaction: Designing Reasonable and Rational Robot Behavior, International Conference on Social Robotics, LNCS, Volume 9979 pp 72-82.
  8. Syed Ali Raza, Jesse Clark, and Mary-Anne Williams. (2016) On Designing Socially Acceptable Reward Shaping, International Conference on Social Robotics, LNCS, Volume 9979 pp 860-869.
  9. Ojha, S. and Williams, M-A, (2016) Ethically-Guided Emotional Responses for Social Robots, International Conference on Social Robotics, LNCS, Volume 9979, pp 233-242.
  10. Raza, R.A., Johnston, B., and Williams, M-A. (2016) Reward from Demonstration in Interactive Reinforcement Learning, Proceedings of the Twenty-Ninth International Florida Artificial Intelligence Research Society Conference, AAAI Press, Menlo Park.
  11. Abidi, Piccardi, M. and Williams M-A (2016) Static Action Recognition by Efficient Greedy Inference', Proceedings of the 2016 IEEE Winter Conference on Applications of Computer Vision, IEEE, USA. Video Presentation.
  12. Ramezani, N. & Williams, M-A. (2015), 'Smooth robot motion with an Optimal Redundancy Resolution for PR2 robot based on an analytic inverse kinematic solution', Humanoid Robots (Humanoids), IEEE-RAS 15th International Conference on Humanoid Robots, IEEE, Seoul, Korea, pp. 338-345
  13. Peppas, P., Williams, M-A, Chopra, S. and Foo, N., (2015). Relevance in Belief RevisionArtificial Intelligence Journal, vol. 229, pp. 126-138
  14. Anshar, M. and Williams, M.A. (2015), Evolving synthetic pain into an adaptive self-awareness framework for robots, Biologically Inspired Cognitive Architectures Journal, Volume 16, April 2016, Pages 8-18.
  15. Vitale, J., Williams, M.-.A., Johnston, B. & Boccignone, G. (2014), Affective facial expression processing via simulation: A probabilistic model, Biologically Inspired Cognitive Architectures, vol. 10, pp. 30-41.
  16. Vitale, J., Williams, M. A., & Johnston, B. (2014). Socially Impaired Robots: Human Social Disorders and Robots' Socio-Emotional Intelligence, in International Conference on Social Robotics (pp. 350-359). Springer International Publishing.
  17. Cabibihan, J.-.J., Williams, M.-.A. & Simmons, R. (2014), When Robots Engage HumansInternational Journal of Social Robotics, vol. 6, no. 3, pp. 311-313.
  18. Raza, S., Haider, S. & Williams, M. 2013, Robot reasoning using first order bayesian networks, Lecture Notes in Computer Science, vol. 8032, no. 1, pp. 1-12.
  19. Al-Sharawneh, J.A., Sinnappan, S. & Williams, M. (2013) Credibility-based twitter social network analysis, Lecture Notes in Computer Science, vol. 7808, no. 1, pp. 323-331.
  20. Novianto, R., Johnston, B.G. & Williams, M-A. (2013), Habituation and sensitisation learning in ASMO cognitive architecture, Lecture Notes in Computer Science, vol.8239, pp.249-259.
  21. Peppas, P., Koutras, C.D. and Williams, M-A, (2012), Maps in Multiple Belief Change
    ACM Transactions on Computational Logic, Volume 13, Number 4; online at http://tocl.acm.org/accepted/MR_Maps_Final.pdf
  22. Bogdanovych, A., Stanton, C.J., Wang, X. & Williams, M-A. (2012), 'Real-Time Human-Robot Interactive Coaching System with Full-Body Control Interface', Lecture Notes in Computer Science, vol. 7416, pp. 562-573.
  23. Williams, M-A. (2012), Robot social intelligence, Lecture Notes in Computer Science, vol. 7621, pp. 45-55.
  24. Stanton, C.J., Ratanasena, E., Haider, S. & Williams, M-A. (2012), Perceiving forces, bumps, and touches from proprioceptive expectations, Lecture Notes in Computer Science, vol. 7416, pp. 377-388.
  25. Goebel, R. & Williams, M-A. (2011), Editorial : The Expansion Continues: Stitching together the Breadth of Disciplines Impinging on Artificial Intelligence, Artificial Intelligence Journal, vol. 175, no. 5-6, pp. 929-929.
  26. Benferhat, S., Dubois, D., Prade, H. & Williams, M-A. (2010), A Framework For Iterated Belief Revision Using Possibilistic Counterparts To Jeffrey'S Rule, Fundamenta Informaticae, vol. 99, no. 2, pp. 147-168.
  27. Williams, M-A, Gärdenfors, P., McCarthy, J., Karol, A., and Stanton, C., (2009). A Grounding Framework, Journal of Autonomous Agents and Multi-Agent Systems, vol. 19, no. 3, pp. 272-296.
  28. Chen, X., Liu, W. & Williams, M-A. (2009), Introduction: Practical Cognitive Agnets and Robots, Autonomous Agents And Multi-Agent Systems, vol. 19, no. 3, pp. 245-247.
  29. Stanton, C.J. & Williams, M-A. (2008), 'Robotics: State of the Art and Future Challenges', Artificial Intelligence Journal, vol. 172, no. 18, pp. 1967-1972.

Social Robotics Undergraduate Dissertations 

  1. Le Kang, The Integration of Web Technologies and Robotics: from Robot Application Development to Social Ability, Honours Thesis, UTS, 2016
  2. Jenny Lui, A Graphical User Interface Based on Shared Knowledge Robotics, Capstone Thesis, 2015. Video Presentation
  3. Michelle Youssef, Human to PR2 Robot Motion Imitation and Recall System, Capstone Thesis, UTS, 26th August 2013, pp. 1-70 Video Presentation 

Social Robotics Postgraduate Dissertations 

  1. Nima, Inverse Kinematics, Kinematic Control and Redundancy Resolution for Chained-Link Robotic Manipulators, 2016
  2. Shaukat Albedi, Semi-supervised and Unsupervised Extensions to Maximum-Margin Structured Prediction, 2016
  3. Wei Wang, Social Network for Robots to Share Information and Skills, 2016.
  4. Novianto, R. Flexible attention-based cognitive architecture for robots, 2015
  5. Edward Wei, Learning how to make good decisions, 2014
  6. Xun Wang, HRMI: an Innovative Framework for Qualitative and Quantitative Risk Management, 2013
  7. Ben Johnston, Practical Commonsense Reasoning, 2011.