Bio:
I'm Mark Yeatman. My professional and academic interests are all things related to Robotics, Human-Machine Interaction, Simulation, Automation, Optimization, and Machine Learning. I received my Doctorate in Mechanical Engineering from The University of Texas at Dallas (UTD) in Fall 2020 and my Bachelor's degree in Mechanical Engineering and Computer Science from UTD in Spring 2015.
Currently, I am employed by the Boston Dynamics AI Institute as an applied scientist.
With some of my freetime, I volunteer as a mentor to the 2173 FIRST robotics team (they could always use more donations from generous sponsors.)
Github:
https://github.com/myeatman-bdai
Linked In:
Google Scholar Profile:
Publications:
Yeatman, M., Lv, G., and Gregg, R. D. "Passivity-Based Control with a Generalized Energy Storage Function for Robust Walking of Biped Robots." Proceedings of the... American Control Conference. 2018. (PDF)
Yeatman, M., Lv, G., and Gregg, R. D. "Decentralized Passivity-Based Control With a Generalized Energy Storage Function for Robust Biped Locomotion." ASME. J. Dyn. Sys., Meas., Control. October 2019 (PDF)
Yeatman, M. and Gregg, R. D. "Using Energy Shaping and Regulation for Generation and Stabilization of Limit Cycles in Simple Locomotive Systems." ASME Journal of Computational Nonlinear Dynamics. 2021 (PDF)
L. R. Reyes et al., "Towards Telementoring for Needle Insertion: Effects of Haptic and Visual Feedback on Mentor Perception of Trainee Forces," 2022 IEEE Haptics Symposium (HAPTICS), 2022
Yeatman, M. R. (2020). Energy and Passivity Based Control for Bipeds and Assistive Walking Devices (Doctoral dissertation). (PDF)
Open Source Software:
