welcome to the
HEATlab
human experience & agent teamwork laboratory @ harvey mudd
Learn More!

Vision

A world in which computational agents intuitively and fluidly navigate the messiness of people's lives.

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 multiple agents, including humans, virtual (computational) agents, and robots (embodied agents). We are particularly motivated by the challenge of coordinating the activities of human-robot teams in environments that require explicit cooperation to be successful. A particular goal for human-robot teamwork is in planning solutions that recognize and exploit the relative strengths of humans and agents to accomplish what neither can achieve alone. Interested? Come visit us in Beckman B115! For the latest HEATlab news and highlights, follow us on social media:

Projects

Click on the project descriptions below for more details about what we do and how you can apply to get involved!
2017 Summer Research Project Descriptions are now available! Apply at: https://www.cs.hmc.edu/research/

Publications

Here is a selection of our publications. Click here for a more comprehensive list.

Robust Execution of Probabilistic Temporal Plans

Lund, Dietrich, Chow, and Boerkoel

Trust and Cooperation in Human-Robot Decision Making

Wu, Paeng, Linder, Valdesolo, and Boerkoel

Robust Execution Strategies for Probabilistic Temporal Planning

Dietrich, Lund, and Boerkoel

Human-Robot Trust and Cooperation Through a Game Theoretic Framework

Paeng, Wu, and Boerkoel

Predicting the Quality of User Experiences to Improve Productivity and Wellness

Donti, Rosenbloom, Gruver, and Boerkoel

Robustness in Probabilistic Temporal Planning

Brooks, Reed, Gruver, and Boerkoel

Exploring Active and Passive Team-Based Coordination

Donti and Boerkoel

Distributed Reasoning for Multiagent Simple Temporal Problems

Boerkoel and Durfee

Towards Control and Sensing for an Autonomous Mobile Robot Assistant Navigating Assembly Lines

Unhelkar, Perez, Boerkoel, Bix, Bartscher, and Shah

Distributed Algorithms for Incrementally Maintaining Multiagent Simple Temporal Networks

Boerkoel, Planken, Wilcox, and Shah

Planning for Flexible Human-Robot Co-navigation in Dynamic Manufacturing Environments

Boerkoel and Shah

Using Hybrid Scheduling for the Semi-Autonomous Formation of Expert Teams

Durfee, Boerkoel, and Sleight

Decoupling the Multiagent Disjunctive Temporal Problem

Boerkoel and Durfee

A Distributed Approach to Summarizing Spaces of Multiagent Schedules

Boerkoel and Durfee

Generalized Solution Techniques for Preference-Based Constrained Optimization with CP-nets

Boerkoel, Durfee, and Purrington

Current Team

Jordan Abrahams '19

Robot Brunch

Brenner Ryan '19

Robot Brunch

Brenda Castro '18

Human Robot Teamwork

Amy Huang '18

PolyBots!

Hamzah Khan '18

Robot Brunch

Liam Lloyd '18

PolyBots!

Montana Roberts, Scripps '18

Human-Robot Teamwork

Jane Wu '18

Human Robot Teamwork

Sam Dietrich '17

Robot Brunch

Emi Reed '17

Robot Brunch; PaWPal

Lab Alumni

Scott Chow '17

Robot Brunch

Kyle Lund '17

Robot Brunch

Erin Paeng '17

Human Robot Teamwork

Sam Echevarria '16

PaWPal

Kari Linder, CMC '16

Human Robot Teamwork

Emma Meersman '16

PaWPal

Priya Donti '15

PaWPal

Alex Gruver '15

PaWPal; Robot Brunch

Jacob Rosenbloom '15

PaWPal

Jeb Brooks '14

Robot Brunch

Contact Us

Want to get involved? Have other ideas? Questions? Please contact us using the form below!

The online application for summer undergradate research positions is posted here each January, so please check back soon!
Please note: there are currently no available positions for independent research, high school student interns or graduate students.

For all other opportunities to get involved, please follow us on social media and join our mailing list!