Congratulations to Junhyeok Ahn for successfully defending his PhD dissertation. You can access the written dissertation by clicking here.
New Work on Climbing Robots with Slippage Conditions
Recap of ASE 389 Human Centered Robotics Class
We had a wonderful semester teaching ASE 389 Decision and Control of Human-Centered Robots. You can find the syllabus below:
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:
New PhD Dissertation on Whole-Body Trajectory Generation and Optimization
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:
New Work on Data-Driven Modeling of Deformable Objects
PI Sentis Teaches New Course on Learning for Dynamics and Controls
New Work on Reactive Synthesis and Motion Planning for Humanoid Robots
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.
New Algorithm Enables Heterogeneous Multi-Robot Search for Missing Objects
In this video, three ground robots — two A1 quadrupeds and one HSR mobile platform — sweep an environment quickly in search of a missing volleyball ball. They achieve this capability by employing online path planning and heterogeneous clustering to accommodate for the different speeds and fields of view of each robot. The algorithm supports up to 50 robot/vehicle search and is robust to robot/vehicle failures by re-planning at runtime. This technology is geared towards tasks such as emergency response where people could be missing during a fire or flood.
New Method Enables Whole-Body Controllers to Become Adaptive to External Disturbances
This work describes an online gain adaptation method to enhance the robustness of whole-body controllers for legged robots under unknown external force disturbances. Without properly accounting for external forces, the closed-loop control system incorporating WBC can easily become unstable, and therefore the desired task goals may not be achievable. The proposed method serves as a low-level controller for tracking whole-body trajectories more robustly than using fixed gain feedback control methods. Link to abstract:
https://www.frontiersin.org/articles/10.3389/frobt.2021.788902/abstract
NSF NRT Fellowships in Ethical AI
Our lab is announcing multiple NSF Ph.D. Fellowships in Ethical AI starting 2022 through 2025! Good Systems, a UT Grand Challenge, and Texas Robotics are recruiting our first cohort of NSF Research Traineeship Ph.D. Fellows in Ethical AI. Prospective students interested in working in the HCRL can apply for doctoral admission in our department. More information can be found under the Fellowship tab: http://shorturl.at/gAEY9.