This paper addresses the problem of dynamic allocation of robot resources to tasks with hierarchical representations and multiple types of execution constraints, with the goal of enabling single-robot multitasking capabilities. Although the vast majority of robot platforms are equipped with more than one sensor (cameras, lasers, sonars) and several actuators (wheels/legs, two arms), which would in principle allow the robot to concurrently work on multiple tasks, existing methods are limited to allocating robots in their entirety to only one task at a time. This approach employs only a subset of a robot's sensors and actuators, leaving other robot resources unused. Our aim is to enable a robot to make full use of its capabilities by having an individual robot multitask, distributing its sensors and actuators to multiple concurrent activities. We propose a new architectural framework based on Hierarchical Task Trees that supports multitasking through a new representation of robot behaviors that explicitly encodes the robot resources (sensors and actuators) and the environmental conditions needed for execution. This architecture was validated on a two-arm, mobile, PR2 humanoid robot, performing tasks with multiple types of execution constraints.

REU Site: Collaborative Human-Robot Interaction for Robots in the Field, National Science Foundation PI: David Feil-Seifer, co-PI: Emily Hand, Amount: $405,000, March 1, 2022 - Feb. 28, 2025

REU Site: Collaborative Human-Robot Interaction, National Science Foundation PI: David Feil-Seifer, co-PI: Shamik Sengupta, Amount: $360,000, Feb. 1, 2018 - Jan. 31, 2022