159 citations · 492 across the 75 of their papers we have counts for
20 papers · 1 filter
Safe Control Under Input Limits with Neural Control Barrier Functions
Simin Liu, Changliu Liu, John Dolan
We propose new methods to synthesize control barrier function (CBF)-based safe controllers that avoid input saturation, which can cause safety violations. In particular, our method…
Probabilistic Safeguard for Reinforcement Learning Using Safety Index Guided Gaussian Process Models
Weiye Zhao, Tairan He, Changliu Liu
Safety is one of the biggest concerns to applying reinforcement learning (RL) to the physical world. In its core part, it is challenging to ensure RL agents persistently satisfy a…
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…
General Place Recognition Survey: Towards the Real-world Autonomy Age
Peng Yin, Shiqi Zhao, Ivan Cisneros +6
Place recognition is the fundamental module that can assist Simultaneous Localization and Mapping (SLAM) in loop-closure detection and re-localization for long-term navigation. The…
Safety Index Synthesis via Sum-of-Squares Programming
Weiye Zhao, Tairan He, Tianhao Wei +2
Control systems often need to satisfy strict safety requirements. Safety index provides a handy way to evaluate the safety level of the system and derive the resulting safe control…
Persistently Feasible Robust Safe Control by Safety Index Synthesis and Convex Semi-Infinite Programming
Tianhao Wei, Shucheng Kang, Weiye Zhao +1
Model mismatches prevail in real-world applications. Ensuring safety for systems with uncertain dynamic models is critical. However, existing robust safe controllers may not be rea…
BioSLAM: A Bio-inspired Lifelong Memory System for General Place Recognition
Peng Yin, Abulikemu Abuduweili, Shiqi Zhao +2
We present BioSLAM, a lifelong SLAM framework for learning various new appearances incrementally and maintaining accurate place recognition for previously visited areas. Unlike hum…
Control Barrier Functions-based Semi-Definite Programs (CBF-SDPs): Robust Safe Control For Dynamic Systems with Relative Degree Two Safety Indices
Jaskaran Singh Grover, Changliu Liu, Katia Sycara
In this draft article, we consider the problem of achieving safe control of a dynamic system for which the safety index or (control barrier function (loosely)) has relative degree…
Social Interactions for Autonomous Driving: A Review and Perspectives
Wenshuo Wang, Letian Wang, Chengyuan Zhang +2
No human drives a car in a vacuum; she/he must negotiate with other road users to achieve their goals in social traffic scenes. A rational human driver can interact with other road…
Safe and Efficient Exploration of Human Models During Human-Robot Interaction
Ravi Pandya, Changliu Liu
Many collaborative human-robot tasks require the robot to stay safe and work efficiently around humans. Since the robot can only stay safe with respect to its own model of the huma…
Efficient Game-Theoretic Planning with Prediction Heuristic for Socially-Compliant Autonomous Driving
Chenran Li, Tu Trinh, Letian Wang +3
Planning under social interactions with other agents is an essential problem for autonomous driving. As the actions of the autonomous vehicle in the interactions affect and are als…
The Before, During, and After of Multi-Robot Deadlock
Jaskaran Grover, Changliu Liu, Katia Sycara
Collision avoidance for multirobot systems is a well-studied problem. Recently, control barrier functions (CBFs) have been proposed for synthesizing controllers that guarantee coll…
ARC - Actor Residual Critic for Adversarial Imitation Learning
Ankur Deka, Changliu Liu, Katia Sycara
Adversarial Imitation Learning (AIL) is a class of popular state-of-the-art Imitation Learning algorithms commonly used in robotics. In AIL, an artificial adversary's misclassifica…
Noncooperative Herding With Control Barrier Functions: Theory and Experiments
Jaskaran Grover, Nishant Mohanty, Wenhao Luo +2
In this paper, we consider the problem of protecting a high-value unit from inadvertent attack by a group of agents using defending robots. Specifically, we develop a control strat…
Robust Task Planning for Assembly Lines with Human-Robot Collaboration
Jessica Leu, Yujiao Cheng, Changliu Liu +1
Efficient and robust task planning for a human-robot collaboration (HRC) system remains challenging. The human-aware task planner needs to assign jobs to both robots and human work…
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…
An Optical Control Environment for Benchmarking Reinforcement Learning Algorithms
Abulikemu Abuduweili, Changliu Liu
Deep reinforcement learning has the potential to address various scientific problems. In this paper, we implement an optics simulation environment for reinforcement learning based…
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…
Transferable and Adaptable Driving Behavior Prediction
Letian Wang, Yeping Hu, Liting Sun +3
While autonomous vehicles still struggle to solve challenging situations during on-road driving, humans have long mastered the essence of driving with efficient, transferable, and…