no code implementations • 7 Mar 2024 • Tairan He, Zhengyi Luo, Wenli Xiao, Chong Zhang, Kris Kitani, Changliu Liu, Guanya Shi
We present Human to Humanoid (H2O), a reinforcement learning (RL) based framework that enables real-time whole-body teleoperation of a full-sized humanoid robot with only an RGB camera.
no code implementations • 31 Jan 2024 • Tairan He, Chong Zhang, Wenli Xiao, Guanqi He, Changliu Liu, Guanya Shi
Legged robots navigating cluttered environments must be jointly agile for efficient task execution and safe to avoid collisions with obstacles or humans.
1 code implementation • 14 Jan 2024 • Zeji Yi, Chaoyi Pan, Guanqi He, Guannan Qu, Guanya Shi
Sampling-based Model Predictive Control (MPC) has been a practical and effective approach in many domains, notably model-based reinforcement learning, thanks to its flexibility and parallelizability.
1 code implementation • 13 Oct 2023 • Kevin Huang, Rwik Rana, Alexander Spitzer, Guanya Shi, Byron Boots
Precise arbitrary trajectory tracking for quadrotors is challenging due to unknown nonlinear dynamics, trajectory infeasibility, and actuation limits.
1 code implementation • 8 Oct 2023 • Wenli Xiao, Tairan He, John Dolan, Guanya Shi
In contrast, policy adaptation based on reinforcement learning (RL) offers versatility and generalizability but presents safety and robustness challenges.
1 code implementation • 6 Oct 2023 • Jacob Sacks, Rwik Rana, Kevin Huang, Alex Spitzer, Guanya Shi, Byron Boots
A major challenge in robotics is to design robust policies which enable complex and agile behaviors in the real world.
no code implementations • 20 May 2023 • Wenqi Cui, Guanya Shi, Yuanyuan Shi, Baosen Zhang
Ensuring the frequency stability of electric grids with increasing renewable resources is a key problem in power system operations.
1 code implementation • 13 May 2022 • Michael O'Connell, Guanya Shi, Xichen Shi, Kamyar Azizzadenesheli, Anima Anandkumar, Yisong Yue, Soon-Jo Chung
Last, our control design extrapolates to unseen wind conditions, is shown to be effective for outdoor flights with only onboard sensors, and can transfer across drones with minimal performance degradation.
no code implementations • 29 Oct 2021 • Weici Pan, Guanya Shi, Yiheng Lin, Adam Wierman
We study a variant of online optimization in which the learner receives $k$-round $\textit{delayed feedback}$ about hitting cost and there is a multi-step nonlinear switching cost, i. e., costs depend on multiple previous actions in a nonlinear manner.
no code implementations • NeurIPS 2021 • Tongxin Li, Ruixiao Yang, Guannan Qu, Guanya Shi, Chenkai Yu, Adam Wierman, Steven H. Low
Motivated by online learning methods, we design a self-tuning policy that adaptively learns the trust parameter $\lambda$ with a competitive ratio that depends on $\varepsilon$ and the variation of system perturbations and predictions.
1 code implementation • NeurIPS 2021 • Guanya Shi, Kamyar Azizzadenesheli, Michael O'Connell, Soon-Jo Chung, Yisong Yue
We provide instantiations of our approach under varying conditions, leading to the first non-asymptotic end-to-end convergence guarantee for multi-task nonlinear control.
no code implementations • 2 Mar 2021 • Michael O'Connell, Guanya Shi, Xichen Shi, Soon-Jo Chung
We validate our approach by flying a drone in an open air wind tunnel under varying wind conditions and along challenging trajectories.
no code implementations • 10 Dec 2020 • Guanya Shi, Wolfgang Hönig, Xichen Shi, Yisong Yue, Soon-Jo Chung
We present Neural-Swarm2, a learning-based method for motion planning and control that allows heterogeneous multirotors in a swarm to safely fly in close proximity.
no code implementations • NeurIPS 2020 • Chenkai Yu, Guanya Shi, Soon-Jo Chung, Yisong Yue, Adam Wierman
We study the impact of predictions in online Linear Quadratic Regulator control with both stochastic and adversarial disturbances in the dynamics.
no code implementations • 16 Nov 2020 • Guanya Shi, Yifeng Zhu, Jonathan Tremblay, Stan Birchfield, Fabio Ramos, Animashree Anandkumar, Yuke Zhu
Deep learning-based object pose estimators are often unreliable and overconfident especially when the input image is outside the training domain, for instance, with sim2real transfer.
no code implementations • 9 May 2020 • Yashwanth Kumar Nakka, Anqi Liu, Guanya Shi, Anima Anandkumar, Yisong Yue, Soon-Jo Chung
The Info-SNOC algorithm is used to compute a sub-optimal pool of safe motion plans that aid in exploration for learning unknown residual dynamics under safety constraints.
no code implementations • 6 Mar 2020 • Guanya Shi, Wolfgang Hönig, Yisong Yue, Soon-Jo Chung
We design a stable nonlinear tracking controller using the learned model.
1 code implementation • NeurIPS 2020 • Guanya Shi, Yiheng Lin, Soon-Jo Chung, Yisong Yue, Adam Wierman
This paper presents competitive algorithms for a novel class of online optimization problems with memory.
no code implementations • L4DC 2020 • Anqi Liu, Guanya Shi, Soon-Jo Chung, Anima Anandkumar, Yisong Yue
To address this challenge, we present a deep robust regression model that is trained to directly predict the uncertainty bounds for safe exploration.
2 code implementations • 19 Nov 2018 • Guanya Shi, Xichen Shi, Michael O'Connell, Rose Yu, Kamyar Azizzadenesheli, Animashree Anandkumar, Yisong Yue, Soon-Jo Chung
To the best of our knowledge, this is the first DNN-based nonlinear feedback controller with stability guarantees that can utilize arbitrarily large neural nets.