Modular autonomous driving systems must coordinate global progress objectives with local safety-driven reactions under imperfect sensing and strict real-time constraints. This paper presents a ROS2-native arbitration module that continuously fuses the outputs of two unchanged and interpretable controllers: a global reference-tracking controller based on Pure Pursuit and a reactive LiDAR-based Gap Follow controller. At each control step, both controllers propose Ackermann commands, and a PPO-trained policy predicts a continuous gate from a compact feature observation to produce a single fused drive command, augmented with practical safety checks. For comparison under identical ROS topic inputs and control rate, we implement a lightweight sampling-based predictive baseline. Robustness is evaluated using a ROS2 impairment protocol that injects LiDAR noise, delay, and dropout, and additionally sweeps forward-cone false short-range outliers. In a repeatable close-proximity passing scenario, we report safe success and failure rates together with per-step end-to-end controller runtime as sensing stress increases. The study is intended as a command-level robustness evaluation in a modular ROS2 setting, not as a replacement for planning-level interaction reasoning.
DeepIPCv2: LiDAR-powered Robust Environmental Perception and Navigational Control for Autonomous Vehicle
Department of Computer Science and Electronics, Universitas Gadjah Mada（计算机科学与电子系，加查马达大学）；Department of Computer Science and Engineering, Toyohashi University of Technology（计算机科学与工程系，toyohashi技术大学）
Institute of Computer Science, University of Tartu（塔尔图大学计算机科学研究所）
The core task of any autonomous driving system is to transform sensory inputs into driving commands. In end-to-end driving, this is achieved via a neural network, with one or multiple cameras as the most commonly used input and low-level driving command, e.g. steering angle, as output. However, depth-sensing has been shown in simulation to make the end-to-end driving task easier. On a real car, combining depth and visual information can be challenging, due to the difficulty of obtaining good spatial and temporal alignment of the sensors. To alleviate alignment problems, Ouster LiDARs can outpu…
SWIFT-Nav: Stability-Aware Waypoint-Level TD3 with Fuzzy Arbitration for UAV Navigation in Cluttered Environments
School of Computer Science and Engineering, University of New South Wales（计算机科学与工程学院，新南威尔士大学）；Escuela de Ingeniería, Universidad Central de Chile（工程学院，智利中央大学）
PERAL: Perception-Aware Motion Control for Passive LiDAR Excitation in Spherical Robots
Centre for Advanced Robotics Technology Innovation (CARTIN), School of Electrical and Electronic Engineering, Nanyang Technological University（先进机器人技术创新中心（CARTIN）、电气与电子工程学院、南洋理工大学）
This paper proposes a framework to measure the important metrics (throughput, delay, packet retransmits, signal strength, etc.) to determine Wi-Fi network performance of mobile robots supported by the Robot Operating Systems (ROS) middleware. We analyze the bidirectional network performance of mobile robots through an experimental setup in an indoor environment, where a mobile robot is communicating vital sensor data such as video streaming from the camera(s) and LiDAR scan values to a command station while it navigates an indoor environment through teleoperated velocity commands received from…
RS2AD: End-to-End Autonomous Driving Data Generation from Roadside Sensor Observations
School of Vehicle and Mobility, Tsinghua University（清华大学车辆与移动系统学院）；State Key Laboratory of Intelligent Green Vehicle and Mobility, Tsinghua University（清华大学智能绿色车辆与移动系统国家重点实验室）；School of Instrumentation and Optoelectronic Engineering, BeiHang University（北航仪器与光电工程学院）；Department of Automation, Tsinghua University（清华大学自动化系）
A Vendor-Agnostic LiDAR Data Conversion System with Multi-Signal Detection and Multi-Format Output
BITS Pilani, Hyderabad Campus（比拉理工学院海德拉巴校区）；Department of Electrical and Electronics Engineering, BITS Pilani, Hyderabad Campus（比拉理工学院海德拉巴校区电气与电子工程系）；Department of Computer Science and Information Systems, BITS Pilani, Hyderabad Campus（比拉理工学院海德拉巴校区计算机科学与信息系统系）
VIRGA: Virtual-Agent-Intermediated Riemannian Geometry for Active-Sensing Air-Ground Coordination
Shanghai Research Institute for Intelligent Autonomous Systems, Tongji University（同济大学上海自主智能无人系统科学中心）；State Key Laboratory of Autonomous Intelligent Unmanned Systems, Tongji University（同济大学自主智能无人系统全国重点实验室）；College of Electronic and Information Engineering, Tongji University（同济大学电子与信息工程学院）
The Irrational Machine: Neurosis and the Limits of Algorithmic Safety
Howard Science Limited, Malvern, UK（霍华德科学有限公司，英国马尔文）；QinetiQ Fellow, UK（QinetiQ Fellow，英国）；Member of Senior Common Room, Pembroke College, University of Oxford（奥克斯福德大学彭伯里学院高级共同房间成员）
End-to-End Humanoid Robot Safe and Comfortable Locomotion Policy
The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））；The Hong Kong University of Science and Technology（香港科技大学）；Human-Robot Interfaces and Interaction Lab., Istituto Italiano di Tecnologia, Italy（人机交互实验室，意大利理工学院）
