Welcome to the Autonomous Systems and Biomechatronics Laboratory. We are part of the Mechanical and Industrial Engineering Department of the University of Toronto. The lab is directed by Professor Goldie Nejat, who is also the Canada Research Chair in Robots for Society.

Our research focuses on developing intelligent mechatronics and robotic systems to assist humans in dangerous and stressful tasks and/or when a shortage of qualified personnel exists. In particular, our research is dedicated to the development of intelligent mechatronics systems with a primary focus on the design of robots and devices. Examples include the design of intelligent robotic systems, sensor agents and devices for search and rescue, exploration, surveillance, human-robot interaction, medical and health care applications.

Our research team is highly interdisciplinary consisting of researchers from both the applied and health sciences.

Research Highlight Papers

Socially Assistive Robots

C. Thompson, S. Mohamed, W. G. Louie, J. Chen He, J. Li, G. Nejat, “The Robot Tangy Facilitating Trivia Games: A Team-based User-Study with Long-Term Care Residents”, IEEE 5th International Symposium on Robotics and Intelligent Sensors (IRIS 2017), pp. 173-178 Oct. 2017. (pdf)

W.G. Louie and G. Nejat “A Persuasive Learning from Demonstration System Architecture for Social Group Recreational Activities,” IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 808-814, 2016. (pdf)

J. Li, W.G. Louie, S. Mohamed, F. Despond, and G. Nejat “A User-Study with Tangy the Bingo Facilitating Robot and Long-Term Care Residents,” International Symposium on Robotics and Intelligent Sensors, Dec. 2016. (pdf)

W.G. Louie, T. Vaquero, G. Nejat and J. C. Beck, "An Autonomous Assistive Robot for Planning, Scheduling and Facilitating Multi-User Activities," 2014 IEEE International Conference on Robotics and Automation (ICRA), pp. 5292-5298, 2014. (pdf)

D. McColl and G. Nejat, “Meal-time with a socially assistive robot and older adults at a long-term care facility,” Special Issue on HRI System Studies in the Journal of Human-Robot Interaction, Vol. 2, No. 1,  pp. 152-171, 2013. (pdf)

D. McColl, W. G. Louie, G. Nejat, “Brian 2.1: A Socially Assistive Robot for the Elderly and Cognitively Impaired,”  Special Issue on Assistive Robotics, IEEE Robotics & Automation Magazine, Vol. 20, No. 1, March 2013. (pdf)

Social Human-Robot Interaction

S. Saunderson and G. Nejat, "Persuasive robots should avoid authority: The effects of formal and real authority on persuasion in human-robot interaction," Science Robotics, vol. 6, no. 58, eabd5186 (2021). (pdf)

S. Saunderson and G. Nejat, “Robots Asking for Favors: The Effects of Directness and Familiarity on Persuasive HRI,” IEEE Robotics and Automation Letters (RA-L), vol. 6, no. 2, pp. 1793-1800, April 2021. (pdf)

S. Saunderson and G. Nejat, "Investigating Strategies for Robot Persuasion in Social Human-Robot Interaction," in IEEE Transactions on Cybernetics, doi: 10.1109/TCYB.2020.2987463. pp. 1-13, May 2020. (pdf)

S. Lin, and G. Nejat, “Robot Evidence Based Search For A Dynamic User In An Indoor Environment,” ASME International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, 2018,  In Print.

D. McColl, G. Jiang, and G. Nejat, “Classifying a Person’s Degree of Accessibility from Natural Body Language During Social Human–Robot Interactions,” IEEE Transactions on Cybernetics, DOI: 10.1109/TCYB.2016.2520367. (pdf)

D. McColl and G. Nejat, “Recognizing Emotional Body Language Displayed by a Human-like Social Robot,” International Journal of Social Robotics, vol. 6, no. 2, pp. 261-280, 2014. (pdf)

D. McColl and G. Nejat, "Affect Detection from Body Language during Social HRI," IEEE International Symposium on Robot and Human Interactive Communication, pp. 1013-1018, Paris, France, Sept. 2012. (pdf)

Robot-Assisted Emergency Response

H. Hu, K. Zhang, A. H. Tan, M. Ruan, C. Agia, and G. Nejat, “A Sim-to-Real Pipeline for Deep Reinforcement Learning for Autonomous Robot Navigation in Cluttered Rough Terrain,” IEEE Robot. Autom. Lett., vol. 6, no. 4, pp. 6569–6576, 2021. (pdf)

F. Niroui, K. Zhang, Z. Kashino, and G. Nejat, “Deep Reinforcement Learning Robot for Search and Rescue Applications: Exploration in Unknown Cluttered Environments,” IEEE Robot. Autom. Lett., vol. 4, no. 2, pp. 610–617, 2019.(pdf)

K. Zhang, F. Niroui, M. Ficocelli and G. Nejat, “Robot Navigation of Environments with Unknown Rough Terrain Using Deep Reinforcement Learning,” IEEE International Symposium on Safety, Security, and Rescue Robotics, 2018. (Best Student Paper Award) (pdf)

B. Doroodgar, Y. Liu  and G. Nejat, “A  Learning-Based Semi-Autonomous Controller for Robotic Exploration of Unknown Disaster Scenes While Searching for Victims,” IEEE Transactions on Cybernetics Part B, Vol. 44, No. 12, 2014. (pdf)

Y. Liu and G. Nejat, “Multi-Robot Cooperative Learning for Semi-autonomous Control in Urban Search and Rescue Applications,” Journal of Field Robotics, Special Issue on Safety, Security, and Rescue Robotics (SSRR),  DOI 10.1002/rob.21597.

3D Sensing

V. Marin, W. Chang and G. Nejat, “Generic Design Methodology for the Development of 3D Structured-light Sensory Systems for Measuring Complex Objects,” Optical Engineering, vol. 53, no. 11, 112210, 2014. (DOI)

B. Mobedi and G. Nejat, “3-D Active Sensing in Time-Critical Urban Search and Rescue Missions,” IEEE/ASME Transactions on  Mechatronics, Vol. 17, No. 6, pp. 1111-1118, 2012. (DOI)

Z. Zhang, G. Nejat, H. Guo, and P. Huang, “A Novel 3D Sensory System for Robot-Assisted Mapping of Cluttered Urban Search and Rescue Environments,” Intelligent Service Robotics, Vol. 4, No. 2, pp. 119-134, 2011. (pdf)

Swarm Robotics 

J. Y. Kim, T.Colaco, Z. Kashino, G. Nejat.and B. Benhabib, "mROBerTO: A Modular Millirobot for Swarm-Behavior Studies,"  IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 2109-2114, 2016. (pdf) 

Research Highlight Videos

A Robot Architecture Using ContextSLAM to Find Products in Unknown Crowded Retail Environments

A Sim-to-Real Pipeline for Deep Reinforcement Learning for Autonomous Robot Navigation in Cluttered Rough Terrain

Persuasive robots should avoid authority: The effects of formal and real authority on persuasion in HRI

Robots Asking for Favors: The Effect of Directness and Familiarity on Persuasive HRI

Robot Navigation of Environments with Unknown Rough Terrain Using Deep Reinforcement Learning

Blueberry Robot: Real-World Robot Search Experiment

mROBerTO: A Modular Millirobot for Swarm-Behavior Studies

Tangy the Socially Assistive Robot Facilitating a Bingo Game:

Casper the Friendly Robot Assisting in the Home:

Leia, the Social Robot Providing Clothing Assistance: