Co-ordinated Tracking and Planning Using Air and Ground Vehicles
نویسندگان
چکیده
The MAV ’08 competition in Agra, India focused on the problem of using air and ground vehicles to locate and rescue hostages being held in a remote building. Executing this mission required addressing a number of technical challenges. The first such technical challenge was the design and operation of a micro air vehicle (MAV) capable of flying the necessary distance and carrying a sensor payload for localizing the hostages. The second technical challenge was the design and implementation of vision and state estimation algorithms to detect and track ground adversaries guarding the hostages. The third technical challenge was the design and implementation of robust planning algorithms that could co-ordinate with the MAV state estimates and generate tactical motion plans for ground vehicles to reach the hostage location without detection by the ground adversaries. In this paper we describe our solutions to these challenges. Firstly, we summarize the design of our micro air vehicle, focusing on the navigation and sensing payload. Secondly, we describe the vision and state estimation algorithms used to track ground features through a sequence of images from the MAV, including stationary obstacles and moving adversaries. Thirdly, we describe the planning algorithm used to generate motion plans to allow the ground vehicles to approach the hostage building undetected by adversaries tracked from the air. Finally, we provide results of our system’s performance during the mission execution.
منابع مشابه
Quadrotor UAV Guidence For Ground Moving Target Tracking
The studies in aerial vehicles modeling and control have been increased rapidly recently. In this paper , a coordination of two types of heterogeneous robots , namely unmanned aerial vehicle (UAV) and unmanned ground vehicle (UGV) is considered. In this paper the UAV plays the role of a virtual leader for the UGVs. The system consists of a vision- based target detection algorithm that uses the ...
متن کاملDevelopment of a strategic plan through SWOT analysis to control traffic-borne air pollutants using CALINE4 model
Traffic is one of the main sources of air pollution in metropolitan areas. With development of transportation system, inappropriate vehicle production, and the use of low-quality fuels, increased pollution in these areas is inevitable. The current study tries to determine PM2.5, PM10, NO2, and CO emission dispersion, caused by traffic, using CALINE4 software. Ac...
متن کاملEvolutionary path planning for autonomous air vehicles using multi-resolution path representation
There is a recognized need for automated path planning for unmanned air vehicles (UAVs) and guided munitions. Evolutionary programming approaches provide an alternative to classical functional optimization methods with the capability of incorporating a variety of optimization goals, while tolerating vehicle constraints. In this work, we introduce an evolutionary flight path planning algorithm c...
متن کاملA generalized form of the Hermite-Hadamard-Fejer type inequalities involving fractional integral for co-ordinated convex functions
Recently, a general class of the Hermit--Hadamard-Fejer inequality on convex functions is studied in [H. Budak, March 2019, 74:29, textit{Results in Mathematics}]. In this paper, we establish a generalization of Hermit--Hadamard--Fejer inequality for fractional integral based on co-ordinated convex functions.Our results generalize and improve several inequalities obtained in earlier studies.
متن کاملOn the Design and Use of a Micro Air Vehicle to Track and Avoid Adversaries
The MAV ’08 competition focused on the problem of using air and ground vehicles to locate and rescue hostages being held in a remote building. To execute this mission, a number of technical challenges were addressed, including designing the micro air vehicle (MAV), using the MAV to geo-locate ground targets, and planning the motion of ground vehicles to reach the hostage location without detect...
متن کامل