Harish Ravichandar

Harish is an Assistant Professor in the School of Interactive Computing at Georgia Institute of Technology. He is also a core faculty member of Georgia Tech’s Institute for Robotics and Intelligent Machines (IRIM).

Harish and his team build structured computational and learning frameworks that contain appropriate inductive biases to improve robots’ efficiency, reliability, and generalizability. His research is motivated by and pertinent to diverse robotics applications, ranging from dexterous manipulation to multi-agent coordination. His work has been recognized by NSF CAREER Award, IEEE MRS Best Paper Award, ASME DSCC Best Student Paper Award, IEEE CSS Video Contest Award, UTC Institute for Advanced System Engineering Graduate Fellowship, and Georgia Tech’s College of Computing Outstanding Post-Doctoral Research and Outstanding Research Scientist Awards.

Papers

• Safe Navigation of Bipedal Robots via Koopman Operator-Based Model Predictive Control — International Conference on Intelligent Robots and Systems (IROS), 2026
• Improving VLA Workspace Randomization Robustness for Industrial Pick-and-Place via Lightweight Residual RL: A Case Study — CVPR Embodied AI Workshop (Oral Spotlight), 2026
• Distributionally Robust Control via Stein Variational Inference for Contact-Rich Manipulation — Robotics: Science and Systems (RSS), 2026
• OmniTacTune: Policy-Agnostic Real-World RL for Tactile Residual Adaptation of Visual Policies — Workshop on Tactile Sensing for Robotic Foundation Models, Robotics: Science and Systems (RSS) - Oral Spotlight, 2026
• Towards Automated Chicken Deboning via Learning-based Dynamically-Adaptive 6-DoF Multi-Material Cutting — International Conference on Robotics and Automation (ICRA), 2026
• Video2Sim2Real: Full-Stack Autonomous Dexterous Skill Acquisition from a Single Human Video — Preprint, 2026
• Going with the Flow: Koopman Behavioral Models as Pseudo Planners for Visuo-Motor Dexterity — Preprint, 2026
• Modeling and Optimizing the Provisioning of Exhaustible Capabilities for Simultaneous Task Allocation and Scheduling — Autonomous Agents and Multi-Agent Systems (AAMAS) - Oral, 2026
• Learning and Optimizing the Efficacy of Spatio-Temporal Task Allocation under Temporal and Resource Constraints — Preprint, 2026
• ImMimic: Cross-Domain Imitation from Human Videos via Mapping and Interpolation — Conference on Robot Learning (CoRL) - Oral, 2025
• JaxRobotarium: Training and Deploying Multi-Robot Policies in 10 Minutes — Conference on Robot Learning (CoRL), 2025
• Capability-Aware Shared Hypernetworks for Flexible Heterogeneous Multi-Robot Coordination — Conference on Robot Learning (CoRL), 2025
• AsymDex: Asymmetry and Relative Coordinates for RL-based Bimanual Dexterity — Preprint, 2025
• On the Surprising Effectiveness of Spectral Clipping in Learning Stable Linear and Latent-Linear Dynamical Systems — Preprint, 2025
• Evaluating and Improving Graph-based Explanation Methods for Multi-Agent Coordination — Autonomous Agents and Multi-Agent Systems (AAMAS) - Extended Abstract, 2025
• Learning Flexible Heterogeneous Coordination With Capability-Aware Shared Hypernetworks — Autonomous Agents and Multi-Agent Systems (AAMAS) - Extended Abstract, 2025
• CIMER: Combining Imitation and Emulation to Learn Prehensile Dexterity from State-only Observations — IEEE International Conference on Robotics and Automation (ICRA), 2025
• Q-ITAGS: Quality-Optimized Spatio-Temporal Heterogeneous Task Allocation with a Time Budget — International Symposium of Robotics Research (ISRR), 2024
• AsymDex: Leveraging Asymmetry and Relative Motion in Learning Bimanual Dexterity — Workshop on Whole-body Control and Bimanual Manipulation: Applications in Humanoids and Beyond, Conference on Robot Learning (CoRL), 2024
• KOROL: Learning Visualizable Object Feature with Koopman Operator Rollout for Manipulation — Conference on Robot Learning (CoRL), 2024
• Learning Prehensile Dexterity by Imitating and Emulating State-only Observations — IEEE Robotics and Automation Letters, 2024
• MARBLER: An Open Platform for Standardized Evaluation of Multi-Robot Reinforcement Learning Algorithms — International Symposium on Multi-Robot & Multi-Agent Systems (MRS) - Best Paper Award, 2023
• Generalization of Heterogeneous Multi-Robot Policies via Awareness and Communication of Capabilities — Conference on Robot Learning (CoRL), 2023
• On the Utility of Koopman Operator Theory in Learning Dexterous Manipulation Skills — Conference on Robot Learning (CoRL) - Oral, 2023
• Risk-Tolerant Task Allocation and Scheduling in Heterogeneous Multi-Robot Team — International Conference on Intelligent Robots and Systems (IROS), 2023
• D-ITAGS: A Dynamic Interleaved Approach to Resilient Task Allocation, Scheduling, and Motion Planning — IEEE Robotics and Automation Letters (RA-L) and International Conference on Intelligent Robots and Systems (IROS), 2023
• The Effects of Robot Motion on Comfort Dynamics of Novice Users in Close-Proximity Human-Robot Interaction — International Conference on Intelligent Robots and Systems (IROS), 2023
• Benefits of Multi-Objective Trajectory Adaptation in Close-Proximity Human-Robot Interaction — IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), 2023
• Concurrent Constrained Optimization of Unknown Rewards for Multi-Robot Task Allocation — Robotics: Science and Systems (RSS), 2023
• A Sampling-based Approach for Heterogeneous Coalition Scheduling with Temporal Uncertainty — Robotics: Science and Systems (RSS), 2023
• Concurrent Constrained Optimization of Unknown Rewards for Multi-Robot Task Allocation — Workshop on Autonomous Robots and Multirobot Systems (ARMS), Autonomous Agents and Multi-Agent Systems (AAMAS), 2023
• Inferring Implicit Trait Preferences from Demonstrations of Task Allocation in Heterogenous Teams — Autonomous Agents and Multi-Agent Systems (AAMAS) - Extended Abstract, 2023
• Neural Geometric Fabrics: Efficiently Learning High-Dimensional Policies from Demonstration — Cornference on Robot Learning (CoRL), 2022
• Learning Trait Preferences for Task allocation in Heterogeneous Multi-Agent Teams — Workshop on Human-Multi-Robot Systems, International Conference on Intelligent Robots and Systems (IROS), 2022
• Leveraging Cognitive States in Human-Robot Teaming — IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), 2022
• Constrained Reinforcement Learning for Dexterous Manipulation — International Workshop on Safe Reinforcement Learning, International Joint Conference on Artificial Intelligence (IJCAI), 2022
• Fast Anticipatory Motion Planning for Close-Proximity Human-Robot Interaction — Workshop on Close Proximity Human-Robot Collaboration, Robotics: Science and Systems (RSS), 2022
• Neural Geometric Fabrics: Efficiently Learning High-Dimensional Policies from Demonstration — Workshop on Overlooked Aspects of Imitation Learning, Robotics: Science and Systems (RSS), 2022
• Resource-Aware Adaptation of Heterogeneous Strategies for Coalition Formation — Autonomous Agents and Multi-Agent Systems (AAMAS) - Extended Abstract, 2022
• Evaluating the Effectiveness of Corrective Demonstrations and a Low-Cost Sensor for Dexterous Manipulation — Machine Learning in Human-Robot Collaboration (MLHRC) Workshop, ACM/IEEE International Conference on Human-Robot Interaction (HRI), 2022
• GRSTAPS: Graphically Recursive Simultaneous Task Allocation, Planning, and Scheduling — International Journal of Robotics Research (IJRR), 2022
• Resilient Coalition Formation in Heterogeneous Teams via Imitation Learning — Workshop on Cognitive and Social Aspects of Human Multi-Robot Interaction, IROS, 2021
• Desperate Times Call for Desperate Measures: Towards Risk-Adaptive Coalition Formation — International Conference on Intelligent Robots and Systems (IROS), 2021
• An Interleaved Approach to Trait-Based Task Allocation and Scheduling — International Conference on Intelligent Robots and Systems (IROS), 2021
• Predicting Individual Human Performance in Human-Robot Teaming — IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), 2021
• STRATA : Unified Framework for Task Assignments in Large Teams of Heterogeneous Agents — International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS)– JAAMAS track, 2021
• Learning Hierarchical Task Networks with Preferences from Unannotated Demonstrations — Conference on Robot Learning (CoRL), 2020
• Human-in-the-Loop Robot Control for Human-Robot Collaboration — IEEE Control Systems Magazine, 2020
• Approximated Dynamic Trait Models for Heterogeneous Multi-Robot Teams — International Conference on Intelligent Robots and Systems (IROS), 2020
• Anticipatory Human-Robot Collaboration via Multi-Objective Trajectory Optimization — International Conference on Intelligent Robots and Systems (IROS), 2020
• STRATA : Unified Framework for Task Assignments in Large Teams of Heterogeneous Agents — Autonomous Agents and Multi-Agent Systems (JAAMAS), 2020
• Recent Advances in Robot Learning from Demonstration — Annual Review of Control, Robotics, and Autonomous Systems, 2020
• Learning and Coordination of Movement Primitives for Bimanual Manipulation Tasks Using Concurrent Synchronization — World Scientific Series: Recent Advances in Industrial Manufacturing, 2020
• Learning Hierarchical Task Networks with Preferences from Unannotated Demonstrations — Conference on Robot Learning (CoRL), 2019
• Taking Recoveries to Task : Recovery-Driven Development for Recipe-based Robot Tasks — International Symposium on Robotics Research (ISRR), 2019
• Skill Acquisition via Automated Multi-Coordinate Cost Balancing — International Conference on Robotics and Automation (ICRA), 2019
• Learning position and orientation dynamics from demonstrations via contraction analysis — Autonomous Robots (AuRo), 2019