Open Human-Robot Collaboration using Decentralized Inverse Reinforcement Learning

The growing interest in human-robot collaboration (HRC), where humans and robots cooperate towards shared goals, has seen significant advancements over the past decade. While previous research has addressed various challenges, several key issues remain unresolved. Many domains within HRC involve activities that do not necessarily require human presence throughout the entire task. Existing literature typically models HRC as a closed system, where all agents are present for the entire duration of the task. In contrast, an open model offers flexibility by allowing an agent to enter and exit the collaboration as needed, enabling them to concurrently manage other tasks. In this paper, we introduce a novel multiagent framework called oDec-MDP, designed specifically to model open HRC scenarios where agents can join or leave tasks flexibly during execution. We generalize a recent multiagent inverse reinforcement learning method - Dec-AIRL to learn from open systems modeled using the oDec-MDP. Our method is validated through experiments conducted in both a simplified toy firefighting domain and a realistic dyadic human-robot collaborative assembly. Results show that our framework and learning method improves upon its closed system counterpart.

Authors

• Prasanth Sengadu Suresh
• Siddarth Jain
• Prashant Doshi
• Diego Romeres

Keywords

• Learning systems
• Toy manufacturing industry
• Human-robot interaction
• Collaboration
• Reinforcement learning
• Open systems
• Intelligent robots
• Assembly
• Inverse Reinforcement Learning
• Human-robot Collaboration
• Operating System
• Closed System
• Task Duration
• Time Step
• Global Status
• Agentic
• Local State
• Kullback-Leibler
• Common Function
• Simulation Trajectories
• Reward Function
• Markov Decision Process
• Transition Function
• Policy Learning
• Simulation Domain
• Set Of Agents
• Team Activities
• Human Preferences
• Open Collaboration
• Expert Demonstrations
• Robotic Agents
• Average Reward
• Subset Of Tasks
• Task Order