Reid Simmons Research Professor Website Office 3213 Newell-Simon Hall Email rsimmons@andrew.cmu.edu Phone (412) 268-2621 Department Robotics Institute Computer Science Department Research Interests Artificial Intelligence Robotics CSD Courses Taught 15482 - Fall, 2025 15482 - Fall, 2024 My research focuses on the area reliable autonomous systems (especially mobile robots) operating in rich, uncertain environments. The goal is to create intelligent systems that can operate autonomously for long periods of time in unstructured, natural environments. This necessitates robots that can plan, reason about uncertainty, diagnose and recover from unanticipated errors, interact with other robots and humans, and learn. I am interested in the use of probabilistic reasoning to explicitly model and plan for uncertainty. I am currently focusing on multi-robot coordination and human-robot social interaction. Multi-Robot Coordination. We are researching issues of how multiple, heterogeneous robots can coordinate to carry out high-level tasks, especially those that cannot be accomplished by a single robot. Issues include having the robots negotiate to dynamically form teams and assign tasks, monitoring each other's performance, and adapting dynamically to changing situations. The work extends traditional three-tiered architectures to multiple robots and extends planning and scheduling algorithms to handle uncertainty and failing plans. Application domains include dexterous, multi-robot large-scale assembly. Human-Robot Social Interaction. The goal here is to make robots more useful and acceptable by enabling them to interact with humans using social rules and conventions. This includes both conversational and spatial social interaction. In the area of conversational interaction, we have developed the roboceptionist, in conjunction with the School of Drama, to have a robot with character and personality interact over long periods of time. In the area of spatial interaction, we are looking at socially appropriate navigation and rhythmic interaction. We are also interested in culturally appropriate interaction. Probabilistic Reasoning in Robotics. We are exploring the use of probabilistic reasoning techniques in controlling autonomous robots. We are investigating methods for making mobile robots more robust and self-reliant, especially using Markov models and partially observable Markov models. Publications Conference Choosing Robot Feedback Style to Optimize Human Exercise Performance 2025 • ACM/IEEE International Conference on Human-Robot Interaction • 00:658-666 Kaushik R, Hata R, Steinfeld A, Simmons R Conference CONFORMALIZED INTERACTIVE IMITATION LEARNING: HANDLING EXPERT SHIFT & INTERMITTENT FEEDBACK 2025 • 13th International Conference on Learning Representations Iclr 2025 • 99133-99146 Zhao M, Simmons R, Admoni H, Ramdas A, Bajcsy A Conference Evaluating Feedback Modality Preferences of Power Wheelchair Users During Manual Robotic Arm Control 2025 • IEEE International Conference on Rehabilitation Robotics • 00:620-627 Styler BK, Jia L, Admoni H, Simmons R, Cooper R, Du N, Ding D Conference Leveraging Large Language Models for Preference-Based Sequence Prediction 2025 519-532 Tecson M, Chen D, Zhao M, Erickson Z, Simmons R Journal Article AIāCARING: National AI Institute for Collaborative Assistance and Responsive Interaction for Networked Groups 2024 • AI Magazine • 45(1):124-130 Chernova S, Mynatt E, Rozga A, Simmons R, Yanco H
Conference Choosing Robot Feedback Style to Optimize Human Exercise Performance 2025 • ACM/IEEE International Conference on Human-Robot Interaction • 00:658-666 Kaushik R, Hata R, Steinfeld A, Simmons R
Conference CONFORMALIZED INTERACTIVE IMITATION LEARNING: HANDLING EXPERT SHIFT & INTERMITTENT FEEDBACK 2025 • 13th International Conference on Learning Representations Iclr 2025 • 99133-99146 Zhao M, Simmons R, Admoni H, Ramdas A, Bajcsy A
Conference Evaluating Feedback Modality Preferences of Power Wheelchair Users During Manual Robotic Arm Control 2025 • IEEE International Conference on Rehabilitation Robotics • 00:620-627 Styler BK, Jia L, Admoni H, Simmons R, Cooper R, Du N, Ding D
Conference Leveraging Large Language Models for Preference-Based Sequence Prediction 2025 519-532 Tecson M, Chen D, Zhao M, Erickson Z, Simmons R
Journal Article AIāCARING: National AI Institute for Collaborative Assistance and Responsive Interaction for Networked Groups 2024 • AI Magazine • 45(1):124-130 Chernova S, Mynatt E, Rozga A, Simmons R, Yanco H