Real-time, Distributed Joint Human-Robot Task Execution

This research addresses the problem of human-robot collaborative task execution for hierarchical task plans. The main contributions are the ability for dynamic allocation of tasks in human-robot teams and opportunistic task execution given different environmental conditions. The human-robot collaborative task is represented in a tree structure which consists of sequential, non-ordering, and alternative paths of execution. The general approach to enable human-robot collaborative task execution is to have the robot maintain an updated, simulated version of the human’s task representation, which is similar to the robot’s own controller for the same task. Continuous peer node message passing between the agents’ task representations enables both to coordinate their task execution, so that they perform the task given its required execution constraints and they do not both work on the same task component. A tea-table task scenario was designed for validation with overlapping and non-overlapping sub-tasks between a human and a Baxter robot.

Role: Main mentor of MS student.

Associated Publications:

• Bashira Akter Anima, Janelle Blankenburg, Mariya Zagainova*, S. Pourya Hoseini A., Muhammed Tawfiq Chowdhury, David Feil-Seifer, Monica Nicolescu, and Mircea Nicolescu. “Collaborative Human-Robot Hierarchical Task Execution with an Activation Spreading Architecture.” In International Conference on Social Robotics (ICSR), Madrid, Spain, Nov 2019. Best Paper Award Finalist. https://jblankenburg.github.io/publication/2019-ICSR