Papers indicated by the solemn emoticon (-_-) are required readings. You will write a paragraph about these readings.
Papers indicated by the zen-like emoticon (^_^) are available for presentation.
Week 1
Anatomy of an HRI Paper (Presented by Instructor)
- Huang et al. (2015). Adaptive Coordination Strategies for Human-Robot Handovers. In Proc. of Robotics: Science and Systems (RSS’2015). [PDF]
- Sisbot et al. (2007). A human aware mobile robot motion planner. IEEE Transactions on Robotics 23(5):874–883. [PDF available with Cornell login]
- Fraune et al. (2015). Three’s company, or a crowd?: The effects of robot number and behavior on HRI in Japan and the USA. In Proc. of Robotics: Science and Systems (RSS’2015). [PDF]
Probability
Russell & Norvig (2020). Artificial Intelligence: a Modern Approach (4th ed.). Prentice Hall. Chapter 12.
Week 2
Bayesian Networks
- Russell & Norvig (2020). Artificial Intelligence: a Modern Approach (4th ed.). Prentice Hall. Chapter 13.
Markov Models + HMMs
- Russell & Norvig (2020). Artificial Intelligence: a Modern Approach (4th ed.). Prentice Hall. Chapter 14
Week 3
Filtering, Kalman Filters, & Particle Filters
- Russell & Norvig (2009). Artificial Intelligence: a Modern Approach (3rd ed.). Prentice Hall. Chapters 15.4 on Kalman Filters and 15.5 (specifically 15.5.3) on Particle Filters
- Thrun, Burgard, & Fox (2005). Probabilistic robotics. MIT Press. Chapters 2-4.
Week 4
Intention Recognition I
- Dennett (1978). True Believers: The Intentional Strategy and Why It Works. In The Intentional Stance, 13-35. MIT Press. [Distributed in Class] (-_-)
- Iregui & Aertbeliën (2021). Reconfigurable constraint-based reactive framework for assistive robotics with adaptable levels of autonomy. IEEE Robotics and Automation Letters, 6(4), 7397-7405. [PDF] (^_^)
- Zhao, Simmons, & Admoni (2022). Coordination With Humans Via Strategy Matching. In 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 9116-9123. [PDF] (^_^)
Decision-Making and MDPs
- Russell & Norvig (2009). Artificial Intelligence: a Modern Approach (3rd ed.). Prentice Hall. Chapters 16.1-3, 17.
- Sutton & Barto (2018). Reinforcement Learning: An Introduction. MIT Press. Chapter 3. Worth reading Chapters 1-2 as well.
- Optional: Thrun, Burgard, & Fox (2005). Probabilistic robotics. MIT Press. Chapter 14.
Week 5
Social Navigation I
- Helbing & Molnar (1995). Social force model for pedestrian dynamics. Physical review E,51(5), 4282. [PDF] (-_-)
- Murakami et al. (2014). Destination unknown: walking side-by-side without knowing the goal. In Proceedings of the ACM/IEEE international conference on Human-robot interaction (HRI’14), 471–478. [PDF] (^_^)
- Kollmitz et al. (2015). Time dependent planning on a layered social cost map for human-aware robot navigation. In Proc. of the 2015 European Conference on Mobile Robots (ECMR), [PDF] (^_^)
Solving MDPs
- Russell & Norvig (2009). Artificial Intelligence: a Modern Approach (3rd ed.). Prentice Hall. Chapter 17.
- Sutton & Barto (2018). Reinforcement Learning: An Introduction. MIT Press. Chapter 4.
- Optional: Thrun, Burgard, & Fox (2005). Probabilistic robotics. MIT Press. Chapter 14.
Week 6
Intention Recognition II
- Xu & Dudek (2015). Optimo: Online probabilistic trust inference model for asymmetric human-robot collaborations. In Proceedings of the Tenth Annual ACM/IEEE International Conference on Human-Robot Interaction (HRI’15), pp. 221-228. [PDF] (^_^)
- Choi, Jawed, & Joo (2022). Preemptive Motion Planning for Human-to-Robot Indirect Placement Handovers. In 2022 International Conference on Robotics and Automation (ICRA), pp. 4743–4749. [PDF] (^_^)
Week 7
Social Navigation II
- Mead & Matarić (2017). Autonomous human–robot proxemics: socially aware navigation based on interaction potential. Autonomous Robots, 41(5), 1189-1201. [PDF] (^_^)
- Bandyopadhyay et al. (2013). Intention-aware motion planning. In Algorithmic Foundations of Robotics X: Proceedings of the Tenth Workshop on the Algorithmic Foundations of Robotics, 475-491. [PDF] (^_^)
Reinforcement Learning I: Monte Carlo Methods and TD Learning
- Artificial Intelligence: a Modern Approach. Russell & Norvig, Prentice Hall (2020, 4th ed.) Chapter 22
- Sutton & Barto (2018). Reinforcement Learning: An Introduction. MIT Press. Chapter 5-6.4
Week 8
Reinforcement Learning II: Q-Learning and Bootstrapping
- Sutton & Barto (2018). Reinforcement Learning: An Introduction. MIT Press. Chapter 6.5-7.
Week 9
Legibility
- Beetz et al. (2010). Generality and legibility in mobile manipulation. Autonomous Robots, 28(1), 21-44. [PDF] (-_-)
- Dragan & Srinivasa (2014). Integrating human observer inferences into robot motion planning. Autonomous Robots, 37(4), 351-368. [PDF] (^_^)
- Szafir et al. (2014). Communication of intent in assistive free flyers. In Proc. of the 2014 ACM/IEEE international conference on Human-robot interaction (HRI’14), pp. 358-365. [PDF] (^_^)
Week 10
Human-Robot Collaboration
- Bratman, M. E. (1992). Shared cooperative activity. The philosophical review, 101(2), 327-341. [PDF] (-_-)
- Hoffman & Breazeal (2007). Cost-based anticipatory action selection for human–robot fluency. IEEE Transactions on Robotics, 23(5), 952-961. [PDF] (^_^)
- Grigore et al. (2018). Preference-based assistance prediction for human-robot collaboration tasks. In 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 4441-4448). [PDF] (^_^)
- Hawkins, et al. (2014). Anticipating human actions for collaboration in the presence of task and sensor uncertainty. In Proc. of the IEEE International Conference on Robotics and Automation (ICRA 2014), pp. 2215-2222 [PDF] (^_^)
- Nikolaidis et al. (2016). Formalizing human-robot mutual adaptation: A bounded memory model. 2016 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI), pp. 75-82. [PDF] (^_^)
Reinforcement Learning III: Approximate Methods
- Sutton & Barto (2018). Reinforcement Learning: An Introduction. MIT Press. Chapter 9-10.
Week 11
Designing Experiments I
- Hoffman & Zhao (2020). A primer for conducting experiments in human–robot interaction. ACM Transactions on Human-Robot Interaction (THRI), 10(1), Sections 1–4. [PDF]
Week 12
Nonverbal Behavior: Gestures
- Ekman & Friesen (1969). The repertoire of nonverbal behavior: Categories, origins, usage, and coding. Semiotica, 1(1), 49-98. [PDF] (-_-)
- Calinon & Billard (2007). Incremental learning of gestures by imitation in a humanoid robot. In Proc. of the ACM/IEEE international conference on Human-robot interaction (HRI’07), pp. 255-262.[PDF] (^_^)
- Ou & Grupen (2010). From manipulation to communicative gesture. In Proceedings of the 5th ACM/IEEE international conference on Human-robot interaction (HRI’10). 325–332. [PDF] (^_^)
- Kwon et al. (2018). Expressing Robot Incapability. In Proceedings of the 2018 ACM/IEEE International Conference on Human-Robot Interaction, 87-95. [PDF] (^_^)
Designing Experiments II
- Hoffman & Zhao (2020). A primer for conducting experiments in human–robot interaction. ACM Transactions on Human-Robot Interaction (THRI), 10(1), Sections 5–11. [PDF]
Week 13
Nonverbal Behavior: Gaze
- Argyle et al. (1973). The different functions of gaze. Semiotica, 7(1), 19-32. [PDF] (-_-)
- Kshirsagar et al. (2020). Robot gaze behaviors in human-to-robot handovers. IEEE Robotics and Automation Letters, 5(4), 6552-6558. [PDF] (^_^)
- Zaraki et al. (2014). Designing and evaluating a social gaze-control system for a humanoid robot. IEEE Transactions on Human-Machine Systems, 44(2), 157-168. [PDF available with Cornell login] (^_^)
Week 14
Learning from Demonstration
- Argall, B. D., Chernova, S., Veloso, M., & Browning, B. (2009). A survey of robot learning from demonstration. Robotics and autonomous systems, 57(5), 469-483. [PDF] (-_-)
- Akgun, B., Cakmak, M., Yoo, J. W., & Thomaz, A. L. (2012). Trajectories and keyframes for kinesthetic teaching: A human-robot interaction perspective. In Proc. of the seventh annual ACM/IEEE international conference on Human-Robot Interaction (HRI’12), pp. 391-398.[PDF] (^_^)
- Niekum et al. (2012). Learning and generalization of complex tasks from unstructured demonstrations. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 5239-5246. [PDF] (^_^)
- Ye G. and Alterovitz R. (2017) Demonstration-Guided Motion Planning. In: Christensen H., Khatib O. (eds) Robotics Research. Springer Tracts in Advanced Robotics, vol 100. [PDF] (^_^)
And that’s not all! There is an additional categorized HRI reading list for motivated students.