Tightly-coupled collaborative human-robot teams
Project lead: Monica Nicolescu
Summary: The goal of this project is to investigate the development of control architectures that enable robots to perform complex tasks in tight collaboration with human teammates. In collaborative domains, in addition to being capable of performing a wide range of tasks, a successful robot team member should take actions that are supportive of and that enhance collaborations. Prior research has investigated the problem of coordinating human-robot teamwork in the context of loosely coupled tasks. However, in practical applications, such as construction, household, assistive domains, a wide range of tasks require a tightly-coupled coordination of teammates. This poses significant challenges related to synchronization of the agents' actions as well as the actual task execution, as teammates need to adjust their actions to each other. The problem of coordinated task execution has been widely addressed in the context of teams consisting only of robot systems. While coordination in a multi-robot system can be achieved through direct messaging across the team, the communication between robots and human teammates has to account for the differences in representations and communication that exist between. In addition, current bidextrous humanoid robotic platforms such as Baxter and PR2, enable the development of multitasking capabilities, in which the robots may concurrently use their two arms as well as the mobile base (when applicable). In the context of tightly-coupled interactions, enabling a robot to multitask raises challenges related to autonomous allocation and coordination of a robot's own actuators in order to avoid conflicting actions. If the robot is working alongside a human teammate, the coordination and synchronization problems become even more complex as they require the ability to perceive/classify the human's actions as well as having an awareness of the task progress and pace. To address the above challenges, this project will investigate the development of robot coordination skills necessary for effective participation in teamwork in tightly-coupled domains.
In particular, we will address the following problems:
- develop single-robot multi-tasking capabilities for bidextrous (and mobile) robots
- develop perceptual skills for real-time classification of human behavior and its pace
- design architectural control mechanisms for synchronization and adaptation of behavior execution for heterogeneous human-robot systems.
Student involvement: The students will begin by studying related work that describes our supporting research, move on to writing simple controllers using our architecture, then proceed to study robot control systems already developed in our group. After this initial stage, the students will proceed with selecting a relevant aspect of multi-agent coordination from the three problem areas listed above. The newly developed capabilities will then be tested on physical robots (Baxter, PR2) performing tasks that require tightly-coupled coordination together with human teammates. This will provide the students with a solid understanding of robot control practices, as well as the challenges of real-time perception and of controlling multi-agent heterogeneous teams.