Timothy Bretl focuses on Motion planning, Robot, Artificial intelligence, Control theory and Sequence. The study incorporates disciplines such as Control engineering and Motion in addition to Robot. His Artificial intelligence study integrates concerns from other disciplines, such as Eddy current and Computer vision.
His research investigates the link between Computer vision and topics such as Probabilistic logic that cross with problems in Simulation and Humanoid robot. In the field of Control theory, his study on Optimal control overlaps with subjects such as Mechanical equilibrium. His studies in Sequence integrate themes in fields like Dynamical systems theory, Limit cycle, Exponential stability, Underactuation and Function.
Timothy Bretl spends much of his time researching Robot, Control theory, Artificial intelligence, Motion planning and Optimal control. His Robot control study in the realm of Robot connects with subjects such as Terrain. His studies examine the connections between Control theory and genetics, as well as such issues in Mobile robot, with regards to Motion control.
He has researched Artificial intelligence in several fields, including Brain–computer interface and Computer vision. His Motion planning research is multidisciplinary, relying on both Iterative method, Configuration space, Sequence, Robot kinematics and Nonholonomic system. His research in Optimal control tackles topics such as Trajectory which are related to areas like Humanoid robot.
Timothy Bretl mainly focuses on Artificial intelligence, Pose, Object, Computer vision and Mri compatible. His Pose study incorporates themes from Robot and Particle filter. In his articles, he combines various disciplines, including Robot and GRASP.
His Particle filter research incorporates elements of Translation, Feature and Rotation. The concepts of his Cognition study are interwoven with issues in Bar and Computer hardware. His Biomedical engineering research is multidisciplinary, incorporating elements of Robotics, Electroencephalography, Wearable computer, Transhumeral prosthesis and Eddy current.
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Materials and Optimized Designs for Human‐Machine Interfaces Via Epidermal Electronics
Jae Woong Jeong;Woon Hong Yeo;Aadeel Akhtar;James J S Norton.
Advanced Materials (2013)
Soft, curved electrode systems capable of integration on the auricle as a persistent brain–computer interface
James J. S. Norton;Dong Sup Lee;Jung Woo Lee;Woosik Lee.
Proceedings of the National Academy of Sciences of the United States of America (2015)
Epidermal mechano-acoustic sensing electronics for cardiovascular diagnostics and human-machine interfaces
Yuhao Liu;James J.S. Norton;Raza Qazi;Zhanan Zou.
Science Advances (2016)
An Epidermal Stimulation and Sensing Platform for Sensorimotor Prosthetic Control, Management of Lower Back Exertion, and Electrical Muscle Activation
Baoxing Xu;Baoxing Xu;Aadeel Akhtar;Yuhao Liu;Hang Chen;Hang Chen.
Advanced Materials (2016)
Motion Planning for Legged Robots on Varied Terrain
Kris K. Hauser;Timothy Bretl;Jean-Claude Latombe;Kensuke Harada.
The International Journal of Robotics Research (2008)
Motion Planning of Multi-Limbed Robots Subject to Equilibrium Constraints: The Free-Climbing Robot Problem
The International Journal of Robotics Research (2006)
Using Motion Primitives in Probabilistic Sample-Based Planning for Humanoid Robots
Kris Hauser;Timothy Wolfe Bretl;Kensuke Harada;Jean Claude Latombe.
international workshop algorithmic foundations robotics (2008)
Testing Static Equilibrium for Legged Robots
T. Bretl;S. Lall.
IEEE Transactions on Robotics (2008)
Large-area MRI-compatible epidermal electronic interfaces for prosthetic control and cognitive monitoring.
Limei Tian;Benjamin Zimmerman;Aadeel Akhtar;Ki Jun Yu.
Nature Biomedical Engineering (2019)
Non-gaited humanoid locomotion planning
K. Hauser;T. Bretl;J.-C. Latombe.
ieee-ras international conference on humanoid robots (2005)
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