Anyskill: Learning open-vocabulary physical skill for interactive agents

J Cui, T Liu, N Liu, Y Yang, Y Zhu… - Proceedings of the …, 2024‏ - openaccess.thecvf.com
Traditional approaches in physics-based motion generation centered around imitation
learning and reward sha** often struggle to adapt to new scenarios. To tackle this …

Tailoring solution accuracy for fast whole-body model predictive control of legged robots

C Khazoom, S Hong, M Chignoli… - IEEE Robotics and …, 2024‏ - ieeexplore.ieee.org
Thanks to recent advancements in accelerating non-linear model predictive control (NMPC),
it is now feasible to deploy whole-body NMPC at real-time rates for humanoid robots …

Walking-by-logic: Signal temporal logic-guided model predictive control for bipedal locomotion resilient to external perturbations

Z Gu, R Guo, W Yates, Y Chen… - … on Robotics and …, 2024‏ - ieeexplore.ieee.org
This study proposes a novel planning framework based on a model predictive control
formulation that incorporates signal temporal logic (STL) specifications for task completion …

Robust-locomotion-by-logic: Perturbation-resilient bipedal locomotion via signal temporal logic guided model predictive control

Z Gu, Y Zhao, Y Chen, R Guo, JK Leestma… - arxiv preprint arxiv …, 2024‏ - arxiv.org
This study introduces a robust planning framework that utilizes a model predictive control
(MPC) approach, enhanced by incorporating signal temporal logic (STL) specifications. This …

Safety-critical coordination for cooperative legged locomotion via control barrier functions

J Kim, J Lee, AD Ames - 2023 IEEE/RSJ International …, 2023‏ - ieeexplore.ieee.org
This paper presents a safety-critical approach to the coordinated control of cooperative
robots locomoting in the presence of fixed (holonomic) constraints. To this end, we leverage …

Hierarchical relaxation of safety-critical controllers: Mitigating contradictory safety conditions with application to quadruped robots

J Lee, J Kim, AD Ames - 2023 IEEE/RSJ International …, 2023‏ - ieeexplore.ieee.org
The safety-critical control of robotic systems often must account for multiple, potentially
conflicting, safety constraints. This paper proposes novel relaxation techniques to address …

Reinforcement learning for reduced-order models of legged robots

YM Chen, H Bui, M Posa - 2024 IEEE International Conference …, 2024‏ - ieeexplore.ieee.org
Model-based approaches for planning and control for bipedal locomotion have a long
history of success. It can provide stability and safety guarantees while being effective in …

Constraint-guided online data selection for scalable data-driven safety filters in uncertain robotic systems

JJ Choi, F Castaneda, W Jung, B Zhang… - arxiv preprint arxiv …, 2023‏ - arxiv.org
As the use of autonomous robots expands in tasks that are complex and challenging to
model, the demand for robust data-driven control methods that can certify safety and stability …

Safe control for soft-rigid robots with self-contact using control barrier functions

ZJ Patterson, W **ao, E Sologuren… - 2024 IEEE 7th …, 2024‏ - ieeexplore.ieee.org
Incorporating both flexible and rigid components in robot designs offers a unique solution to
the limitations of traditional rigid robotics by enabling both compliance and strength. This …

A data-driven method for safety-critical control: Designing control barrier functions from state constraints

J Lee, J Kim, AD Ames - 2024 American Control Conference …, 2024‏ - ieeexplore.ieee.org
This paper addresses the challenge of integrating explicit hard constraints into the control
barrier function (CBF) framework for ensuring safety in autonomous systems, including …