3 citations · 10 across the 24 of their papers we have counts for
24 papers
-Reachability: Geometric-Horizon Safety Bellman Equations for Humanoid Safety
Rui Chen, Shangtao Li, Yifan Sun +1
We introduce -Reachability, a scalable approach to Hamilton--Jacobi safety analysis for high-dimensional robotic systems. Unlike prior discounted formulations that rely on fixed…
Dexterous Safe Control for Humanoids in Cluttered Environments via Projected Safe Set Algorithm
Rui Chen, Yifan Sun, Changliu Liu
It is critical to ensure safety for humanoid robots in real-world applications without compromising performance. In this paper, we consider the problem of dexterous safety, featuri…
SPARK: Safe Protective and Assistive Robot Kit
Yifan Sun, Rui Chen, Kai S. Yun +6
This paper introduces the Safe Protective and Assistive Robot Kit (SPARK), a comprehensive benchmark designed to ensure safety in humanoid autonomy and teleoperation. Humanoid robo…
Continual Learning and Lifting of Koopman Dynamics for Linear Control of Legged Robots
Feihan Li, Abulikemu Abuduweili, Yifan Sun +3
The control of legged robots, particularly humanoid and quadruped robots, presents significant challenges due to their high-dimensional and nonlinear dynamics. While linear systems…
Absolute State-wise Constrained Policy Optimization: High-Probability State-wise Constraints Satisfaction
Weiye Zhao, Feihan Li, Yifan Sun +4
Enforcing state-wise safety constraints is critical for the application of reinforcement learning (RL) in real-world problems, such as autonomous driving and robot manipulation. Ho…
Safe Control of Quadruped in Varying Dynamics via Safety Index Adaptation
Kai S. Yun, Rui Chen, Chase Dunaway +2
Varying dynamics pose a fundamental difficulty when deploying safe control laws in the real world. Safety Index Synthesis (SIS) deeply relies on the system dynamics and once the dy…
Constrained Bandwidth Observation Sharing for Multi-Robot Navigation in Dynamic Environments via Intelligent Knapsack
Anirudh Chari, Rui Chen, Han Zheng +1
Multi-robot navigation is increasingly crucial in various domains, including disaster response, autonomous vehicles, and warehouse and manufacturing automation. Robot teams often m…
Meta-Control: Automatic Model-based Control Synthesis for Heterogeneous Robot Skills
Tianhao Wei, Liqian Ma, Rui Chen +2
The requirements for real-world manipulation tasks are diverse and often conflicting; some tasks require precise motion while others require force compliance; some tasks require av…
Absolute Policy Optimization
Weiye Zhao, Feihan Li, Yifan Sun +3
In recent years, trust region on-policy reinforcement learning has achieved impressive results in addressing complex control tasks and gaming scenarios. However, contemporary state…
An Optimal Control Framework for Influencing Human Driving Behavior in Mixed-Autonomy Traffic
Anirudh Chari, Rui Chen, Jaskaran Grover +1
As autonomous vehicles (AVs) become increasingly prevalent, their interaction with human drivers presents a critical challenge. Current AVs lack social awareness, causing behavior…
Safety Index Synthesis with State-dependent Control Space
Rui Chen, Weiye Zhao, Changliu Liu
This paper introduces an approach for synthesizing feasible safety indices to derive safe control laws under state-dependent control spaces. The problem, referred to as Safety Inde…
Learn With Imagination: Safe Set Guided State-wise Constrained Policy Optimization
Yifan Sun, Feihan Li, Weiye Zhao +3
Deep reinforcement learning (RL) excels in various control tasks, yet the absence of safety guarantees hampers its real-world applicability. In particular, explorations during lear…
State-wise Constrained Policy Optimization
Weiye Zhao, Rui Chen, Yifan Sun +2
Reinforcement Learning (RL) algorithms have shown tremendous success in simulation environments, but their application to real-world problems faces significant challenges, with saf…
Proactive Human-Robot Co-Assembly: Leveraging Human Intention Prediction and Robust Safe Control
Ruixuan Liu, Rui Chen, Abulikemu Abuduweili +1
Human-robot collaboration (HRC) is one key component to achieving flexible manufacturing to meet the different needs of customers. However, it is difficult to build intelligent rob…
GUARD: A Safe Reinforcement Learning Benchmark
Weiye Zhao, Yifan Sun, Feihan Li +4
Due to the trial-and-error nature, it is typically challenging to apply RL algorithms to safety-critical real-world applications, such as autonomous driving, human-robot interactio…
Robust and Context-Aware Real-Time Collaborative Robot Handling via Dynamic Gesture Commands
Rui Chen, Alvin Shek, Changliu Liu
This paper studies real-time collaborative robot (cobot) handling, where the cobot maneuvers an object under human dynamic gesture commands. Enabling dynamic gesture commands is us…
State-wise Safe Reinforcement Learning: A Survey
Weiye Zhao, Tairan He, Rui Chen +2
Despite the tremendous success of Reinforcement Learning (RL) algorithms in simulation environments, applying RL to real-world applications still faces many challenges. A major con…
Space-Time Conflict Spheres for Constrained Multi-Agent Motion Planning
Anirudh Chari, Rui Chen, Changliu Liu
Multi-agent motion planning (MAMP) is a critical challenge in applications such as connected autonomous vehicles and multi-robot systems. In this paper, we propose a space-time con…
Task-Agnostic Adaptation for Safe Human-Robot Handover
Ruixuan Liu, Rui Chen, Changliu Liu
Human-robot interaction (HRI) is an important component to improve the flexibility of modern production lines. However, in real-world applications, the task (\ie the conditions tha…
Safe Interactive Industrial Robots using Jerk-based Safe Set Algorithm
Ruixuan Liu, Rui Chen, Changliu Liu
The need to increase the flexibility of production lines is calling for robots to collaborate with human workers. However, existing interactive industrial robots only guarantee int…
A Composable Framework for Policy Design, Learning, and Transfer Toward Safe and Efficient Industrial Insertion
Rui Chen, Chenxi Wang, Tianhao Wei +1
Delicate industrial insertion tasks (e.g., PC board assembly) remain challenging for industrial robots. The challenges include low error tolerance, delicacy of the components, and…
Learning from Physical Human Feedback: An Object-Centric One-Shot Adaptation Method
Alvin Shek, Bo Ying Su, Rui Chen +1
For robots to be effectively deployed in novel environments and tasks, they must be able to understand the feedback expressed by humans during intervention. This can either correct…
Learn from Human Teams: a Probabilistic Solution to Real-Time Collaborative Robot Handling with Dynamic Gesture Commands
Rui Chen, Alvin Shek, Changliu Liu
We study real-time collaborative robot (cobot) handling, where the cobot maneuvers a workpiece under human commands. This is useful when it is risky for humans to directly handle t…
Grounding Implicit Goal Description for Robot Indoor Navigation Via Recursive Belief Update
Rui Chen, Jinxin Zhao, Liangjun Zhang
Natural language-based robotic navigation remains a challenging problem due to the human knowledge of navigation constraints, and destination is not directly compatible with the ro…