New Techniques for Facilitating Improvisational Human-Robot Teams

When robots team up with humans, we want to give human teammates as many possibilities as we can for completing their activities.  However, robustly reacting to and controlling for all the different things a human teammate could do is actually very difficult! In this project, we will build on previous work (see attached representative publication) that defines the concept of improvisational teamwork in order to:

  • Explore new and existing problem formulations (likely various forms of mixed-integer linear programs) that model the variability and uncertainty that human teammates introduce in collaborative human-robot tasks;
  • Develop new algorithms and approaches for reacting to the uncertainty that a human teammate introduces, particularly focusing on providing the human with greater choice and autonomy;
  • Gain inspiration and insights from mathematical fields such as geometry, graph theory, and most notably, operations research; and
  • Extend or adapt existing temporal plan quality metrics to handle scheduling situations that involve uncertainty, preferences, or choice.
Name of research group, project, or lab
Human Experience & Agent Teamwork Lab (HEATlab)
Why join this research group or lab?

The mission of the HEATlab is to create new techniques for human-robot teaming—the flexible navigation and coordination of complex, inter-related activities in shared spaces. We focus on using ideas from AI to automate the scheduling and coordination of human-robot teams. We are particularly motivated by the challenge of coordinating the activities of human-robot teams in environments that require explicit cooperation to be successful. Our goal is to create human-robot teams that exploit the relative strengths of humans and agents to accomplish what neither can achieve alone.

 Learn More about the HEATlab:

Representative publication
Logistics Information:
Project categories
Computer Science
Artificial Intelligence
Operations Research
Student ranks applicable
Student qualifications

Have an active interest/relevant experience in some of the following: operations research, algorithms and algorithm design, graph theory, geometry, and mathematical modeling.

Time commitment
Summer - Full Time
Paid Research
Number of openings
Techniques learned

You will gain experience in all stages of conducting academic research (formulating research questions, designing approaches and evaluations, and evaluating and writing up results). You will also gain experience in operations research, algorithms and algorithm design, graph theory, geometry, and mathematical modeling.

Contact Information:
Mentor name
Jim Boerkoel
Mentor email
Mentor position
Associate Professor of Computer Science
Name of project director or principal investigator
Jim Boerkoel
Email address of project director or principal investigator
2 sp. | 11 appl.
Hours per week
Summer - Full Time
Project categories
Algorithms (+4)
Computer ScienceAlgorithmsArtificial IntelligenceOperations ResearchRobotics