b'Changliu Liu'

research

∙ 09/20/2023

Simulation-aided Learning from Demonstration for Robotic LEGO Construction

Recent advancements in manufacturing have a growing demand for fast, aut...

0 Ruixuan Liu, et al. ∙

research

∙ 09/05/2023

A Lightweight and Transferable Design for Robust LEGO Manipulation

LEGO is a well-known platform for prototyping pixelized objects. However...

0 Ruixuan Liu, et al. ∙

research

∙ 08/25/2023

Learn With Imagination: Safe Set Guided State-wise Constrained Policy Optimization

Deep reinforcement learning (RL) excels in various control tasks, yet th...

0 Weiye Zhao, et al. ∙

research

∙ 08/20/2023

Robotic Planning under Hierarchical Temporal Logic Specifications

Past research into robotic planning with temporal logic specifications, ...

0 Xusheng Luo, et al. ∙

research

∙ 08/06/2023

Customizing Textile and Tactile Skins for Interactive Industrial Robots

Tactile skins made from textiles enhance robot-human interaction by loca...

0 Bo-Ying Su, et al. ∙

research

∙ 07/30/2023

Interactive Car-Following: Matters but NOT Always

Following a leading vehicle is a daily but challenging task because it r...

0 Chengyuan Zhang, et al. ∙

research

∙ 06/21/2023

State-wise Constrained Policy Optimization

Reinforcement Learning (RL) algorithms have shown tremendous success in ...

0 Weiye Zhao, et al. ∙

research

∙ 06/20/2023

Proactive Human-Robot Co-Assembly: Leveraging Human Intention Prediction and Robust Safe Control

Human-robot collaboration (HRC) is one key component to achieving flexib...

0 Ruixuan Liu, et al. ∙

research

∙ 05/25/2023

Robotic LEGO Assembly and Disassembly from Human Demonstration

This paper studies automatic prototyping using LEGO. To satisfy individu...

0 Ruixuan Liu, et al. ∙

research

∙ 05/23/2023

GUARD: A Safe Reinforcement Learning Benchmark

Due to the trial-and-error nature, it is typically challenging to apply ...

0 Weiye Zhao, et al. ∙

research

∙ 04/18/2023

Hybrid Task Constrained Planner for Robot Manipulator in Confined Environment

Trajectory generation in confined environment is crucial for wide adopti...

0 Yifan Sun, et al. ∙

research

∙ 04/12/2023

Robust and Context-Aware Real-Time Collaborative Robot Handling via Dynamic Gesture Commands

This paper studies real-time collaborative robot (cobot) handling, where...

0 Rui Chen, et al. ∙

research

∙ 03/24/2023

Safe and Sample-efficient Reinforcement Learning for Clustered Dynamic Environments

This study proposes a safe and sample-efficient reinforcement learning (...

0 Hongyi Chen, et al. ∙

research

∙ 03/17/2023

Zero-shot Transferable and Persistently Feasible Safe Control for High Dimensional Systems by Consistent Abstraction

Safety is critical in robotic tasks. Energy function based methods have ...

0 Tianhao Wei, et al. ∙

research

∙ 02/06/2023

State-wise Safe Reinforcement Learning: A Survey

Despite the tremendous success of Reinforcement Learning (RL) algorithms...

0 Weiye Zhao, et al. ∙

research

∙ 02/05/2023

Space-Time Conflict Spheres for Constrained Multi-Agent Motion Planning

Multi-agent motion planning (MAMP) is a critical challenge in applicatio...

0 Anirudh Chari, et al. ∙

research

∙ 01/24/2023

AutoCost: Evolving Intrinsic Cost for Zero-violation Reinforcement Learning

Safety is a critical hurdle that limits the application of deep reinforc...

0 Tairan He, et al. ∙

research

∙ 01/14/2023

First Three Years of the International Verification of Neural Networks Competition (VNN-COMP)

This paper presents a summary and meta-analysis of the first three itera...

0 Christopher Brix, et al. ∙

research

∙ 01/09/2023

Distributed Multirobot Control for Non-Cooperative Herding

In this paper, we consider the problem of protecting a high-value area f...

0 Nishant Mohanty, et al. ∙

research

∙ 12/20/2022

The Third International Verification of Neural Networks Competition (VNN-COMP 2022): Summary and Results

This report summarizes the 3rd International Verification of Neural Netw...

0 Mark Niklas Müller, et al. ∙

research

∙ 11/20/2022

Safe Control Under Input Limits with Neural Control Barrier Functions

We propose new methods to synthesize control barrier function (CBF)-base...

0 Simin Liu, et al. ∙

research

∙ 10/03/2022

Probabilistic Safeguard for Reinforcement Learning Using Safety Index Guided Gaussian Process Models

Safety is one of the biggest concerns to applying reinforcement learning...

0 Weiye Zhao, et al. ∙

research

∙ 09/20/2022

Task-Agnostic Adaptation for Safe Human-Robot Handover

Human-robot interaction (HRI) is an important component to improve the f...

0 Ruixuan Liu, et al. ∙

research

∙ 09/19/2022

Safety Index Synthesis via Sum-of-Squares Programming

Control systems often need to satisfy strict safety requirements. Safety...

0 Weiye Zhao, et al. ∙

research

∙ 09/14/2022

Robust Safe Control for Uncertain Dynamic Models

Model mismatches prevail in real-world applications. Hence it is importa...

0 Tianhao Wei, et al. ∙

research

∙ 09/09/2022

General Place Recognition Survey: Towards the Real-world Autonomy Age

Place recognition is the fundamental module that can assist Simultaneous...

2 Peng Yin, et al. ∙

research

∙ 08/30/2022

BioSLAM: A Bio-inspired Lifelong Memory System for General Place Recognition

We present BioSLAM, a lifelong SLAM framework for learning various new a...

11 Peng Yin, et al. ∙

research

∙ 08/25/2022

Control Barrier Functions-based Semi-Definite Programs (CBF-SDPs): Robust Safe Control For Dynamic Systems with Relative Degree Two Safety Indices

In this draft article, we consider the problem of achieving safe control...

0 Jaskaran Singh Grover, et al. ∙

research

∙ 08/16/2022

Social Interactions for Autonomous Driving: A Review and Perspective

No human drives a car in a vacuum; she/he must negotiate with other road...

0 Wenshuo Wang, et al. ∙

research

∙ 08/01/2022

Safe and Efficient Exploration of Human Models During Human-Robot Interaction

Many collaborative human-robot tasks require the robot to stay safe and ...

0 Ravi Pandya, et al. ∙

research

∙ 07/08/2022

Efficient Game-Theoretic Planning with Prediction Heuristic for Socially-Compliant Autonomous Driving

Planning under social interactions with other agents is an essential pro...

0 Chenran Li, et al. ∙

research

∙ 06/05/2022

ARC – Actor Residual Critic for Adversarial Imitation Learning

Adversarial Imitation Learning (AIL) is a class of popular state-of-the-...

13 Ankur Deka, et al. ∙

research

∙ 06/03/2022

The Before, During, and After of Multi-Robot Deadlock

Collision avoidance for multirobot systems is a well-studied problem. Re...

0 Jaskaran Grover, et al. ∙

research

∙ 04/22/2022

Noncooperative Herding With Control Barrier Functions: Theory and Experiments

In this paper, we consider the problem of protecting a high-value unit f...

0 Jaskaran Grover, et al. ∙

research

∙ 04/17/2022

Robust Task Planning for Assembly Lines with Human-Robot Collaboration

Efficient and robust task planning for a human-robot collaboration (HRC)...

0 Jessica Leu, et al. ∙

research

∙ 04/06/2022

Safe Interactive Industrial Robots using Jerk-based Safe Set Algorithm

The need to increase the flexibility of production lines is calling for ...

0 Ruixuan Liu, et al. ∙

research

∙ 03/23/2022

An Optical Controlling Environment and Reinforcement Learning Benchmarks

Deep reinforcement learning has the potential to address various scienti...

0 Abulikemu Abuduweili, et al. ∙

research

∙ 03/09/2022

Learning from Physical Human Feedback: An Object-Centric One-Shot Adaptation Method

For robots to be effectively deployed in novel environments and tasks, t...

0 Alvin Shek, et al. ∙

research

∙ 03/06/2022

A Composable Framework for Policy Design, Learning, and Transfer Toward Safe and Efficient Industrial Insertion

Delicate industrial insertion tasks (e.g., PC board assembly) remain cha...

0 Rui Chen, et al. ∙

research

∙ 02/10/2022

Transferable and Adaptable Driving Behavior Prediction

While autonomous vehicles still struggle to solve challenging situations...

0 Letian Wang, et al. ∙

research

∙ 12/11/2021

Learn from Human Teams: a Probabilistic Solution to Real-Time Collaborative Robot Handling with Dynamic Gesture Commands

We study real-time collaborative robot (cobot) handling, where the cobot...

0 Rui Chen, et al. ∙

research

∙ 12/09/2021

Online Adaptation of Neural Network Models by Modified Extended Kalman Filter for Customizable and Transferable Driving Behavior Prediction

High fidelity behavior prediction of human drivers is crucial for effici...

0 Letian Wang, et al. ∙

research

∙ 11/25/2021

Learn Zero-Constraint-Violation Policy in Model-Free Constrained Reinforcement Learning

In the trial-and-error mechanism of reinforcement learning (RL), a notor...

0 Haitong Ma, et al. ∙

research

∙ 11/15/2021

Joint Synthesis of Safety Certificate and Safe Control Policy using Constrained Reinforcement Learning

Safety is the major consideration in controlling complex dynamical syste...

0 Haitong Ma, et al. ∙

research

∙ 11/01/2021

Hierarchical Adaptable and Transferable Networks (HATN) for Driving Behavior Prediction

When autonomous vehicles still struggle to solve challenging situations ...

0 Letian Wang, et al. ∙

research

∙ 10/03/2021

Safe Control with Neural Network Dynamic Models

Safety is critical in autonomous robotic systems. A safe control law ens...

0 Tianhao Wei, et al. ∙

research

∙ 08/31/2021

The Second International Verification of Neural Networks Competition (VNN-COMP 2021): Summary and Results

This report summarizes the second International Verification of Neural N...

6 Stanley Bak, et al. ∙

research

∙ 08/16/2021

IADA: Iterative Adversarial Data Augmentation Using Formal Verification and Expert Guidance

Neural networks (NNs) are widely used for classification tasks for their...

0 Ruixuan Liu, et al. ∙

research

∙ 08/14/2021

A Microscopic Pandemic Simulator for Pandemic Prediction Using Scalable Million-Agent Reinforcement Learning

Microscopic epidemic models are powerful tools for government policy mak...

0 Zhenggang Tang, et al. ∙

research

∙ 08/04/2021

Tolerance-Guided Policy Learning for Adaptable and Transferrable Delicate Industrial Insertion

Policy learning for delicate industrial insertion tasks (e.g., PC board ...

0 Boshen Niu*, et al. ∙

Changliu Liu

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