Designing cyber-physical systems is a complex task which requires insights at multiple abstraction levels. The choices of single components are deeply interconnected and need to be jointly studied. In this work, we consider the problem of co-designing the control algorithm as well as the platform around it. In particular, we leverage a monotone theory of co-design to formalize variations of the LQG control problem as monotone feasibility relations. We then show how this enables the embedding of control co-design problems in the higher level co-design problem of a robotic platform. We illustrate the properties of our formalization by analyzing the co-design of an autonomous drone performing search-and-rescue tasks and show how, given a set of desired robot behaviors, we can compute Pareto efficient design solutions.
Teaching Autonomous Systems Hands-On: Leveraging Modular Small-Scale Hardware in the Robotics Classroom
University of Pennsylvania（宾夕法尼亚大学）；Technical University of Munich（慕尼黑工业大学）；Lehigh University（理海大学）；University of Texas Austin（德克萨斯大学奥斯汀分校）；Poznan University of Technology（波兹南理工大学）；University of Virginia（弗吉尼亚大学）；Clemson University（克莱姆森大学）；Toyota Research Institute（丰田研究院）
Perception Imitation: Towards Synthesis-free Simulator for Autonomous Vehicles
The Chinese University of Hong Kong（香港中文大学）；Shanghai Artificial Intelligence Laboratory（上海人工智能实验室）；Tongji University（同济大学）；Centre for Perceptual and Interactive Intelligence Limited（感知与交互智能中心有限公司）
Robust and Safe Multi-Agent Reinforcement Learning with Communication for Autonomous Vehicles: From Simulation to Hardware
Department of ECE University of Connecticut（电子工程系，康涅狄格大学）；School of Computing University of Connecticut（计算学院，康涅狄格大学）；Department of ECE Boston University（电子工程系，波士顿大学）
Open-Source Autonomous Driving System Analysis and Multi-Disciplinary Hardware-in-the-Loop Research Paradigm with Reinforcement-Learning Testing and Large Language Models
School of Cyberspace Science and Technology, Beijing Jiaotong University（北京交通大学网络空间科学与技术学院）；School of Information Engineering, Chang’an University（长安大学信息工程学院）
DepthVision: Enabling Robust Vision-Language Models with GAN-Based LiDAR-to-RGB Synthesis for Autonomous Driving
Chair of Robotics, Artificial Intelligence and Real-time Systems, Technical University of Munich（机器人学、人工智能与实时系统教授会，慕尼黑技术大学）；Computer Science and Engineering Department, University of California Merced（计算机科学与工程系，加州大学默塞德分校）
Autonomous Vehicles on the Edge: A Survey on Autonomous Vehicle Racing
University of Pennsylvania（宾夕法尼亚大学）；ETH Zurich（苏黎世联邦理工学院）；California Institute of Technology（加州理工学院）；Technical University of Munich（慕尼黑工业大学）；University of Virginia（弗吉尼亚大学）；Clemson University（克莱姆森大学）
ForzaETH Race Stack -- Scaled Autonomous Head-to-Head Racing on Fully Commercial off-the-Shelf Hardware
ETH Zürich（苏黎世联邦理工学院）；Center for Project-Based Learning (PBL), ETH Zürich（苏黎世联邦理工学院项目式学习中心）；Institute for Dynamic Systems and Control (IDSC), ETH Zürich（苏黎世联邦理工学院动态系统与控制研究所）
Vision based hardware-software real-time control system for autonomous landing of an UAV
AGH University of Science and Technology（AGH科技大学）
在本文中，我们提出了一种基于视觉的硬件-软件控制系统，使自主着陆的多旋翼无人机（UAV）。它允许对1280 x 720@60 fps视频流实时的【形】检测标记的着陆垫。此外，激光雷达传感器用于测量地面以上的高度。异构Zynq SoC设备被用作计算平台。该解决方案在多个序列上进行了测试，着陆垫的检测准确率为96%。该研究表明，可重编程异构计算系统是一个很好的解决方案，无人机，因为它使实时的【形】数据流处理，相对较低的能耗。
Sensor-Driven Mission Synthesis for UAV/UGV Swarms: A TB-CSPN Coordination Architecture with Hardware-Enforced Safety
Institute for Software Technology, University of the Bundeswehr Munich（慕尼黑联邦国防军大学软件技术研究所）；Department of Computer Science, Sapienza University of Rome（罗马大学计算机科学系）；SofTware And Knowledge Engineering Lab（软件与知识工程实验室）
First and High Order Sliding Mode-Multimodel Stabilizing Control Synthesis using Single and Several Sliding Surfaces for Nonlinear Systems: Simulation on an Autonomous Underwater Vehicles (AUV)
Ecole Polytechnique de Tunisie（突尼斯高等理工学院）；L.S.A Laboratoire des Systèmes Avancés（先进系统实验室）
