Zobrazeno 1 - 10
of 5 464
pro vyhledávání: '"Grizzle A"'
This work explores an innovative algorithm designed to enhance the mobility of underactuated bipedal robots across challenging terrains, especially when navigating through spaces with constrained opportunities for foot support, like steps or stairs.
Externí odkaz:
http://arxiv.org/abs/2403.02486
Autor:
Marija Debeljak, Soonweng Cho, Bradley M. Downs, Michael Considine, Brittany Avin-McKelvey, Yongchun Wang, Phillip N. Perez, William E. Grizzle, Katherine A. Hoadley, Charles F. Lynch, Brenda Y. Hernandez, Paul J. van Diest, Wendy Cozen, Ann S. Hamilton, Debra Hawes, Edward Gabrielson, Ashley Cimino-Mathews, Liliana D. Florea, Leslie Cope, Christopher B. Umbricht
Publikováno v:
Breast Cancer Research, Vol 26, Iss 1, Pp 1-15 (2024)
Abstract Background Ductal carcinoma in-situ (DCIS) is a pre-invasive form of invasive breast cancer (IBC). Due to improved breast cancer screening, it now accounts for ~ 25% of all breast cancers. While the treatment success rates are over 90%, this
Externí odkaz:
https://doaj.org/article/a106b36b520948e78078f14a3c21f70b
This paper presents a novel approach to fall prediction for bipedal robots, specifically targeting the detection of potential falls while standing caused by abrupt, incipient, and intermittent faults. Leveraging a 1D convolutional neural network (CNN
Externí odkaz:
http://arxiv.org/abs/2309.14546
Autor:
Jenkins, Odest Chadwicke, Grizzle, Jessy, Atkins, Ella, Stirling, Leia, Rouse, Elliott, Guzdial, Mark, Provost, Damen, Mann, Kimberly, Millunchick, Joanna
The Robotics Major at the University of Michigan was successfully launched in the 2022-23 academic year as an innovative step forward to better serve students, our communities, and our society. Building on our guiding principle of "Robotics with Resp
Externí odkaz:
http://arxiv.org/abs/2308.06905
A new control paradigm using angular momentum and foot placement as state variables in the linear inverted pendulum model has expanded the realm of possibilities for the control of bipedal robots. This new paradigm, known as the ALIP model, has shown
Externí odkaz:
http://arxiv.org/abs/2307.02448
Autor:
Mungai, M. Eva, Grizzle, Jessy
For legged robots to operate in complex terrains, they must be robust to the disturbances and uncertainties they encounter. This paper contributes to enhancing robustness through the design of fall detection/prediction algorithms that will provide su
Externí odkaz:
http://arxiv.org/abs/2303.15620
For bipedal humanoid robots to successfully operate in the real world, they must be competent at simultaneously executing multiple motion tasks while reacting to unforeseen external disturbances in real-time. We propose Kinodynamic Fabrics as an appr
Externí odkaz:
http://arxiv.org/abs/2303.04279
This paper presents a reactive planning system that allows a Cassie-series bipedal robot to avoid multiple non-overlapping obstacles via a single, continuously differentiable control barrier function (CBF). The overall system detects an individual ob
Externí odkaz:
http://arxiv.org/abs/2301.01906
This work reports on developing a deep inverse reinforcement learning method for legged robots terrain traversability modeling that incorporates both exteroceptive and proprioceptive sensory data. Existing works use robot-agnostic exteroceptive envir
Externí odkaz:
http://arxiv.org/abs/2207.03034
Multi-objective or multi-destination path planning is crucial for mobile robotics applications such as mobility as a service, robotics inspection, and electric vehicle charging for long trips. This work proposes an anytime iterative system to concurr
Externí odkaz:
http://arxiv.org/abs/2205.14853