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This work combines control barrier functions (CBFs) with a whole-body controller to enable self-collision avoidance for the MIT Humanoid. Existing reactive controllers for self-collision avoidance cannot guarantee collision-free…

Robotics · Computer Science 2022-11-08 Charles Khazoom , Daniel Gonzalez-Diaz , Yanran Ding , Sangbae Kim

Cyber-physical and autonomous systems are often equipped with mechanisms that provide predictions/projections of future disturbances, e.g., road curvatures, commonly referred to as preview or lookahead, but this preview information is…

Systems and Control · Electrical Eng. & Systems 2024-03-08 Tarun Pati , Seunghoon Hwang , Sze Zheng Yong

In this article, we propose a control architecture for the safe, coordinated operation of a multi-agent system with aerial (UAVs) and ground (UGVs) robots in a confined task space. We consider the case where the aerial and ground operations…

Safe motion planning is essential for autonomous vessel operations, especially in challenging spaces such as narrow inland waterways. However, conventional motion planning approaches are often computationally intensive or overly…

In robotics, control barrier function (CBF)-based safety filters are commonly used to enforce state constraints. A critical challenge arises when the relative degree of the CBF varies across the state space. This variability can create…

Systems and Control · Electrical Eng. & Systems 2025-04-09 Lukas Brunke , Siqi Zhou , Francesco D'Orazio , Angela P. Schoellig

Multi-quadrotor systems face significant challenges in decentralized control, particularly with safety and coordination under sensing and communication limitations. State-of-the-art methods leverage Control Barrier Functions (CBFs) to…

Robotics · Computer Science 2024-09-27 Manohari Goarin , Guanrui Li , Alessandro Saviolo , Giuseppe Loianno

The rapid advancement of robotics necessitates robust tools for developing and testing safe control architectures in dynamic and uncertain environments. Ensuring safety and reliability in robotics, especially in safety-critical…

Robotics · Computer Science 2024-07-19 Hardik Parwana , Mitchell Black , Georgios Fainekos , Bardh Hoxha , Hideki Okamoto , Danil Prokhorov

We present a perception-driven safety filter that converts each 3D Gaussian Splat (3DGS) into a closed-form forward collision cone, which in turn yields a first-order control barrier function (CBF) embedded within a quadratic program (QP).…

Robotics · Computer Science 2025-09-19 Dario Tscholl , Yashwanth Nakka , Brian Gunter

Control barrier functions (CBFs) have a well-established theory in Euclidean spaces, yet still lack general formulations and constructive synthesis tools for systems evolving on manifolds common in robotics and aerospace applications. In…

Systems and Control · Electrical Eng. & Systems 2025-10-24 Massimiliano de Sa , Pio Ong , Aaron D. Ames

Robots operating in everyday environments must navigate and manipulate within densely cluttered spaces, where physical contact with surrounding objects is unavoidable. Traditional safety frameworks treat contact as unsafe, restricting…

Deploying self-navigating surface vessels in inland waterways offers a sustainable alternative to reduce road traffic congestion and emissions. However, navigating confined waterways presents unique challenges, including narrow channels,…

Robotics · Computer Science 2025-09-09 Sajad Ahmadi , Hossein Nejatbakhsh Esfahani , Javad Mohammadpour Velni

Control barrier functions (CBFs) are important in safety-critical systems and robot control applications. Neural networks have been used to parameterize and synthesize CBFs with bounded control input for complex systems. However, it is…

Robotics · Computer Science 2024-10-23 Hanjiang Hu , Yujie Yang , Tianhao Wei , Changliu Liu

Multi-robot systems (MRS) are essential for large-scale applications such as disaster response, material transport, and warehouse logistics, yet ensuring robust, safety-aware formation control in cluttered and dynamic environments remains a…

Robotics · Computer Science 2026-05-06 Qintong Xie , Weishu Zhan , Peter Chin

We propose a unified framework to fast generate a safe optimal control action for a new task from existing controllers on Multi-Agent Systems (MASs). The control action composition is achieved by taking a weighted mixture of the existing…

Systems and Control · Electrical Eng. & Systems 2021-09-22 Lin Song , Neng Wan , Aditya Gahlawat , Chuyuan Tao , Naira Hovakimyan , Evangelos A. Theodorou

In leader-follower consensus, strong r-robustness of the communication graph provides a sufficient condition for followers to achieve consensus in the presence of misbehaving agents. Previous studies have assumed that robots can form and/or…

Robotics · Computer Science 2025-04-14 Haejoon Lee , Dimitra Panagou

Control Barrier Functions (CBFs) have emerged as efficient tools to address the safe navigation problem for robot applications. However, synthesizing informative and obstacle motion-aware CBFs online using real-time sensor data remains…

Robotics · Computer Science 2025-12-02 Xin Yin , Chenyang Liang , Yanning Guo , Jie Mei

In this paper, we propose a method to avoid "no-solution" situations of the control barrier function (CBF) for distributed collision avoidance in a multiagent autonomous robotic system (MARS). MARS, which is composed of distributed…

Robotics · Computer Science 2023-11-14 Hiroki Etchu , Yuki Origane , Daisuke Kurabayashi

Control Barrier Functions (CBFs) can provide provable safety guarantees for dynamic systems. However, finding a valid CBF for a system of interest is often non-trivial, especially for systems having low computational resources, higher-order…

Robotics · Computer Science 2026-03-06 Mattias Trende , Petter Ögren

Researchers have developed various cascaded controllers and non-cascaded controllers for the navigation and control of quadrotors in recent years. It is vital to ensure the safety of a quadrotor both in normal state and in abnormal state if…

Systems and Control · Electrical Eng. & Systems 2022-07-26 Weifeng Zeng , Huanhui Cao , Wenjie Lu , Hao Xiong

Ensuring safe exploration in high-dimensional systems with unknown dynamics remains a significant challenge. Existing safe reinforcement learning methods often provide safety guarantees only in expectation, which can still lead to safety…

Machine Learning · Computer Science 2026-04-28 Rahul Narava , Siddharth Verma , Ojas Jain , Shashi Shekhar Jha , Mayank Shekhar Jha
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