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Robomechanics Lab
Добавлен 12 июн 2017
The Robomechanics Lab at Carnegie Mellon University is working to take robots out of the lab and factory and into challenging real world environments, such as rocky hills and cluttered houses. We use the word “robomechanics” to mean the study of the mechanics of robot behaviors, analogous to the field of biomechanics for natural systems. We are interested in the mechanics of how a robot interacts with that environment to produce a useful behavior. The Robomechanics Lab conducts research in legged and wheeled mobile robotics, mechanism design, feedback control, computer vision, motion planning, and applications of robotics research to search & rescue, planetary exploration, manufacturing, science, and personal assistance.
Robust and Adaptive Rough Terrain Navigation Through Training in Varied Simulated Dynamics
We propose a model-based reinforcement learning approach for robust and adaptive long-horizon navigation in rough terrain environments. Offline, we train an adaptive dynamics model using a wide range of simulated systems. This model can adapt to any new system using state-transition observations from that system. Predictions from the model capture uncertainty about the system's exact dynamics stemming from insufficient observations. Online, we use a divergence constrained path planner to find routes that are robust to the robot's current understanding of dynamics. In our results, we show this allows for long-horizon driving strategies that are conservative when state-transition observatio...
Просмотров: 224
Видео
Pay Attention to How You Drive: Safe and Adaptive Model-Based RL for Off-Road Driving
Просмотров 1987 месяцев назад
Autonomous off-road driving is challenging as risky actions taken by the robot may lead to catastrophic damage. As such, developing controllers in simulation is often desirable as it provides a safer and more economical alternative. However, accurately modeling robot dynamics is difficult due to the complex robot dynamics and terrain interactions in unstructured environments. Domain randomizati...
Convergent iLQR for Safe Trajectory Planning and Control of Legged Robots - ICRA 2024
Просмотров 4328 месяцев назад
In order to perform highly dynamic and agile maneuvers, legged robots typically spend time in underactuated domains (e.g. with feet off the ground) where the system has limited command of its acceleration and a constrained amount of time before transitioning to a new domain (e.g. foot touchdown). Meanwhile, these transitions can instantaneously change the system's state, possibly causing pertur...
LORIS: A Lightweight Free-Climbing Robot for Extreme Terrain Exploration - Presentation
Просмотров 4578 месяцев назад
"LORIS: A Lightweight Free-Climbing Robot for Extreme Terrain Exploration," Paul Nadan, Spencer Backus, and Aaron M. Johnson, in IEEE International Conference on Robotics and Automation, May, 2024. CMU Robotics Institute: www.ri.cmu.edu/publications/loris-a-lightweight-free-climbing-robot-for-extreme-terrain-exploration/ Climbing robots can investigate scientifically valuable sites that convent...
Conflict-based Model Predictive Control for Scalable Multi-Robot Motion Planning
Просмотров 2768 месяцев назад
This work presents a scalable and dynamically-feasible approach for generating motion plans for multiple robots simultaneously.
LORIS: A Lightweight Free-Climbing Robot for Extreme Terrain Exploration
Просмотров 17 тыс.8 месяцев назад
"LORIS: A Lightweight Free-Climbing Robot for Extreme Terrain Exploration," Paul Nadan, Spencer Backus, and Aaron M. Johnson, in IEEE International Conference on Robotics and Automation, May, 2024. CMU Robotics Institute: www.ri.cmu.edu/publications/loris-a-lightweight-free-climbing-robot-for-extreme-terrain-exploration/ Climbing robots can investigate scientifically valuable sites that convent...
The Simplest Walking Robot: A bipedal robot with one actuator and two rigid bodies
Просмотров 1,4 тыс.Год назад
The Simplest Walking Robot: A bipedal robot with one actuator and two rigid bodies
Hybrid iLQR Model Predictive Control for Contact Implicit Stabilization on Legged Robots
Просмотров 510Год назад
Model predictive control (MPC) is a popular strategy for controlling robots but is difficult for systems with contact due to the complex nature of hybrid dynamics. To implement MPC for systems with contact, dynamic models are often simplified or contact sequences fixed in time in order to plan trajectories efficiently. In this work, we propose the hybrid iterative linear quadratic regulator (iL...
Proprioception and reaction for walking among entanglements
Просмотров 4 тыс.Год назад
Legged robots get snagged on entanglements like vines and cords. Can they detect these entanglement and quickly get unstuck? This is the talk presented by Justin Yim for our paper at the 2023 International Conference on Intelligent Robots and Systems: Justin K. Yim, Jiming Ren, David Ologan, Selvin Garcia Gonzalez, and Aaron M. Johnson "Proprioception and reaction for walking among entanglement...
Staged Contact Optimization: Combining Contact-Implicit and Multi-Phase Hybrid Trajectory Opt.
Просмотров 289Год назад
Presentation for IROS 2023 paper: Michael R. Turski, Joseph Norby, and Aaron M. Johnson. "Staged Contact Optimization: Combining Contact-Implicit and Multi-Phase Hybrid Trajectory Optimization." In IEEE/RSJ International Conference on Intelligent Robots and Systems, October 2023 Trajectory optimization problems for legged robots are commonly formulated with fixed contact schedules. These multi-...
Proprioception and Tail Control Enable Extreme Terrain Traversal by Quadruped Robots - Presentation
Просмотров 220Год назад
Presentation for IROS 2023 paper: Yanhao Yang, Joseph Norby, Justin K. Yim, and Aaron M. Johnson. "Proprioception and Tail Control Enable Extreme Terrain Traversal by Quadruped Robots." In IEEE/RSJ International Conference on Intelligent Robots and Systems, October 2023 Abstract: Legged robots leverage ground contacts and the reaction forces they provide to achieve agile locomotion. However, un...
Proprioception and Tail Control Enable Extreme Terrain Traversal by Quadruped Robots
Просмотров 2,4 тыс.Год назад
Legged robots leverage ground contacts and the reaction forces they provide to achieve agile locomotion. However, uncertainty coupled with contact discontinuities can lead to failure, especially in real-world environments with unexpected height variations such as rocky hills or curbs. To enable dynamic traversal of extreme terrain, this work introduces 1) a proprioception-based gait planner for...
Off-Nominal Rover Driving: Terrain Manipulation and Degraded Mobility Compensation
Просмотров 663Год назад
Catherine Pavlov's thesis defense. Planetary exploration rovers are at the forefront of the exploration of our solar system, but their mobility in soft soils beyond nominal operation is poorly understood. A better understanding of wheel-soil interaction lets us do more with rovers in two key ways: 1) add manipulation capabilities through the use of nonprehensile manipulation, e.g. by using whee...
The Uncertainty Aware Salted Kalman Filter
Просмотров 3072 года назад
"The Uncertainty Aware Salted Kalman Filter: State Estimation for Hybrid Systems with Uncertain Guards," J. Joe Payne, Nathan J. Kong, and Aaron M. Johnson, in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October, 2022. arxiv.org/abs/2202.12729 We present a method for updating robotic state belief through contact with uncertain surfaces and apply this update to a ...
Microspine Design for Additive Manufacturing
Просмотров 6092 года назад
Microspine Design for Additive Manufacturing
Increasing the reliability of legged robots in the presence of uncertainty
Просмотров 8732 года назад
Increasing the reliability of legged robots in the presence of uncertainty
Panel Discussion 2 - RSS 2022: The Science of Bumping Into Things
Просмотров 1682 года назад
Panel Discussion 2 - RSS 2022: The Science of Bumping Into Things
Pulkit Agrawal - RSS 2022: The Science of Bumping Into Things
Просмотров 4152 года назад
Pulkit Agrawal - RSS 2022: The Science of Bumping Into Things
Zachary Manchester - RSS 2022: The Science of Bumping Into Things
Просмотров 4922 года назад
Zachary Manchester - RSS 2022: The Science of Bumping Into Things
Alessandro Saccon - RSS 2022: The Science of Bumping Into Things
Просмотров 3402 года назад
Alessandro Saccon - RSS 2022: The Science of Bumping Into Things
Yan Gu - RSS 2022: The Science of Bumping Into Things
Просмотров 3442 года назад
Yan Gu - RSS 2022: The Science of Bumping Into Things
Yuki Shirai - RSS 2022: The Science of Bumping Into Things
Просмотров 1342 года назад
Yuki Shirai - RSS 2022: The Science of Bumping Into Things
Taylor Howell and Simon Le Cleac'h - RSS 2022: The Science of Bumping Into Things
Просмотров 2582 года назад
Taylor Howell and Simon Le Cleac'h - RSS 2022: The Science of Bumping Into Things
Panel Discussion 1 - RSS 2022: The Science of Bumping Into Things
Просмотров 932 года назад
Panel Discussion 1 - RSS 2022: The Science of Bumping Into Things
Kevin Lynch - RSS 2022: The Science of Bumping Into Things
Просмотров 2022 года назад
Kevin Lynch - RSS 2022: The Science of Bumping Into Things
Huanbo Sun - RSS 2022: The Science of Bumping Into Things
Просмотров 1102 года назад
Huanbo Sun - RSS 2022: The Science of Bumping Into Things
Ken Goldberg - RSS 2022: The Science of Bumping Into Things
Просмотров 1952 года назад
Ken Goldberg - RSS 2022: The Science of Bumping Into Things
Maria Bauza - RSS 2022: The Science of Bumping Into Things
Просмотров 2812 года назад
Maria Bauza - RSS 2022: The Science of Bumping Into Things