Difference between revisions of "Robotics"
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A SQUID drone can be launched in ballistically from a cannon or tube, unfold in mid-flight, and stabilize itself. To the left you can see a diagram of '''SQUID I''' and photographs of '''SQUID 2''' in the folded and unfolded states. | A SQUID drone can be launched in ballistically from a cannon or tube, unfold in mid-flight, and stabilize itself. To the left you can see a diagram of '''SQUID I''' and photographs of '''SQUID 2''' in the folded and unfolded states. | ||
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+ | === Preference Based Learning for Exoskeleton Personalization === | ||
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+ | In preference based learning, only a human subject's relative preference between two different settings is available for learning feedback. In collaboration with Prof. [http://www.yisongyue.com/ Yisong Yue] we have been developing techniques for preference learning in both bandit and RL settings. With The Ames Group, we have applied these preference learning techniques to the problem of learning and optimizing the parameters of exoskeleton gaits so that user comfort is optimized. | ||
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=== Neural Prosthetics and Brain-Machine Interfaces === | === Neural Prosthetics and Brain-Machine Interfaces === | ||
A neural prosthesis is a ''direct brain interface'' that enables a human, via the use of surgically | A neural prosthesis is a ''direct brain interface'' that enables a human, via the use of surgically |
Latest revision as of 02:03, 12 January 2021
The Burdick Group Wiki Home Page
Robotics and Spinal Cord Therapy
Burdick Research Group: Robotics & BioEngineering
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Current and Recent Research Topics
DARPA Subterranean ChallengeWe are part of Team CoSTAR (lead by NASA/Jet Propulsion Laboratory, with partners MIT, KAIST, LTU), competing in the Subterranean Challenge (www.subtchallenge.com). See the Team's web site for the latest information. |
Preference Based Learning for Exoskeleton PersonalizationIn preference based learning, only a human subject's relative preference between two different settings is available for learning feedback. In collaboration with Prof. Yisong Yue we have been developing techniques for preference learning in both bandit and RL settings. With The Ames Group, we have applied these preference learning techniques to the problem of learning and optimizing the parameters of exoskeleton gaits so that user comfort is optimized. |
Axel and DuAxel Rovers for extreme planetary terrainsConventional robotic Martian explorers, such as Sojourner, Spirit, and Opportunity, have sufficient mobility to access ~60% of the Martian surface. However, some of the most interesting science targets occur in the currently inaccessible extreme terrains, such as steep craters, overhangs, loose soil, and layered stratigraphy. Access to extreme terrains on other planets (besides Mars) and moons is also of potential interest. In collaboration with JPL, we are developing the Axel and DuAxel rovers. Axel is a minimalist tethered robot that can ascend and descend vertical and steeps slopes, as well as navigate over large (relative to the body size) obstacles. In the DuAxel configuration, two Axels dock with a central module to form a self-contained 4-wheeled rover, which can then disassemble as needed to allow one or both Axels to descend into extreme terrain. The goal of this work is to develop and demonstrate the motion planning, novel mobility mechanisms, mobility analysis, and steep terrain sampling technologies that would allow Axel and DuAxel to be viable concepts for future scientific missions to extreme terrains. |
Locomotion Rehabilitation After Severe Spinal Cord InjuryMore than 250,000 people in the U.S. suffer from a major Spinal Cord Injury (SCI), and over 11,000 new people will be afflicted each year. Our lab collaborates with Prof. Reggie Edgerton at UCLA to develop new therapies and new technologies that hopefully one day will enable patients suffering from SCI to partially or fully recover the ability to walk. Currently, we focus on these topics: |
Recent PapersPast Research TopicsHere are a some recent research topics that were actively pursued in our group.
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