Here we share our recent research on performing multi-robot search in outdoor and indoor environments.

Link to paper
Link to project website

Congratulations to Minkyu Kim for successfully defending his Ph.D. dissertation exploring the navigation of single and teams of robots in human environments. (Click here or on the images to access the PDF).

 

Congratulations to Junhyeok Ahn for successfully defending his PhD dissertation. You can access the written dissertation by clicking here.

Congratulations to Jee-Eun for her new paper accepted in Frontiers in Robotics and AI, titled: “Safe Robot Climbing in Unknown Structures”. The work is a collaboration with Tirtha Bandyopadhyay from Australia’s CSIRO Data61 group. While the paper is in press, you can view the video below:

We had a wonderful semester teaching ASE 389 Decision and Control of Human-Centered Robots. You can find the syllabus below:

Link to Class Syllabus

In addition, students pursued projects in human-centered robotics focusing mostly on trajectory generation and control. Here is a video presentation of one of the projects:

Ph.D. student Jaemin Lee defended his dissertation which addresses problems at the intersection of trajectory generation, optimization, and control of humanoid robots. You can find a link to his Ph.D. thesis here:

 

 

Our paper “Mixtures of Controlled Gaussian Processes for Dynamical Modeling of Deformable Objects” has been accepted for the Learning for Dynamics & Control Conference, 2022. Congratulations to Ce Xu and our collaborators at the Polytechnic University of Catalonia (UPC)!

 

Here is a video of the content of the class and selected project presentations:

Ye Zhao, Yinan Li, Luis Sentis, Ufuk Topcu, Jun Liu, Reactive Task and Motion Planning for Robust Whole-Body Dynamic Locomotion in Constrained Environments, The International Journal of Robotics Research, In Press 2022

This study takes a first step toward formally and reactively task planning and whole-body dynamic loco-manipulation behaviors in constrained and dynamically changing environments. We formulate a two-player temporal logic game between the multi-limb locomotion planner and its dynamic environment to synthesize a winning strategy that delivers symbolic locomotion actions. A controller further executes low-level motion primitives that generate feasible locomotion trajectories.