https://blog.pouceheure.fr/tags/ground_robot/Recent content in Ground_robot on Hugo POUSSEURHugoenSun, 01 Jan 2023 00:00:00 +0000https://blog.pouceheure.fr/articles/cooperative-architecture/Sun, 01 Jan 2023 00:00:00 +0000https://blog.pouceheure.fr/articles/cooperative-architecture/Abstract A cooperative navigation architecture for the search and recognition of targets using aerial and ground vehicles is proposed in this paper. The architecture allows managing aerial and ground vehicles to autonomously perform different tasks independently or cooperatively. For our application, two main tasks are conceived: aerial monitoring of a surface to search for targets and target ground recognition. In the target aerial detection task, the aerial drone autonomously follows a trajectory computed to cover the entire surface to be monitored, searching for targets using vision algorithms.https://blog.pouceheure.fr/projects/multi-robots/Wed, 10 Aug 2022 00:00:00 +0000https://blog.pouceheure.fr/projects/multi-robots/Context As part of a research internship project, a modular ROS architecture was designed to enable cooperative navigation between heterogeneous autonomous vehicles: drones (UAVs) and ground robots (UGVs). The contribution focused on supporting the development and implementation of this system, which aimed to be scalable, with dynamic task allocation and coordinated execution across different hardware platforms. The architecture uses a unified communication protocol, distributed ROS nodes, and a namespace layout allowing multiple robots to be managed from a central ROS master.https://blog.pouceheure.fr/articles/gradient-descent/Sat, 01 Jan 2022 00:00:00 +0000https://blog.pouceheure.fr/articles/gradient-descent/Abstract Avoiding obstacles is a key feature in a vehicle autonomous navigation methodology. The Dynamic Window Approach (DWA), proposed several decades ago, has emerged as a responsive navigation methodology suitable for reactive obstacle avoidance. In the initial approach of the DWA, the optimization of an objective function is realized with an exhaustive computation, which can be costly in computational time. This is not useful in a real-time scenario where an autonomous vehicle needs to avoid obstacles in urban or road velocity conditions.https://blog.pouceheure.fr/articles/motion-control/Sat, 01 Jan 2022 00:00:00 +0000https://blog.pouceheure.fr/articles/motion-control/Abstract In this paper, a navigation control for a platoon composed of a ground and an aerial vehicle is proposed. The aim of this work is to define a platooning system that exploits the advantages of both types of robots: while the aerial drone is faster and is not affected by the terrain, the ground vehicle has more autonomy and can carry heavier payloads. The proposed control system allows the aerial vehicle to follow the ground vehicle, maintaining a desired relative position, and to assist in navigation by providing information about the environment.https://blog.pouceheure.fr/projects/dwa-optimization/Fri, 10 Dec 2021 00:00:00 +0000https://blog.pouceheure.fr/projects/dwa-optimization/Overview The Dynamic Window Approach (DWA) is a reactive motion planning method used in mobile robotics. At each control cycle, it samples admissible velocity pairs $(v, \omega)$ and evaluates them using an objective function, selecting the pair with the highest score. The original method presents two main issues: Discrete sampling, which limits precision High computational cost in evaluation loops These limitations can be addressed by defining a convex, differentiable objective function and applying gradient descent for continuous optimization.