A High Performance Fuzzy Logic Architecture for UAV Decision Making

The majority of Unmanned Aerial Vehicles (UAVs) in operation today are not truly autonomous, but are instead reliant on a remote human pilot. A high degree of autonomy can provide many advantages in terms of cost, operational resources and safety. However, one of the challenges involved in achieving autonomy is that of replicating the reasoning and decision making capabilities of a human pilot. One candidate method for providing this decision making capability is fuzzy logic. In this role, the fuzzy system must satisfy real-time constraints, process large quantities of data and relate to large knowledge bases. Consequently, there is a need for a generic, high performance fuzzy computation platform for UAV applications. Based on Lees’ [1] original work, a high performance fuzzy processing architecture, implemented in Field Programmable Gate Arrays (FPGAs), has been developed and is shown to outclass the performance of existing fuzzy processors

Service-Oriented Architecture for Space Exploration Robotic Rover Systems

Currently, industrial sectors are transforming their business processes into e-services and component-based architectures to build flexible, robust, and scalable systems, and reduce integration-related maintenance and development costs. Robotics is yet another promising and fast-growing industry that deals with the creation of machines that operate in an autonomous fashion and serve for various applications including space exploration, weaponry, laboratory research, and manufacturing. It is in space exploration that the most common type of robots is the planetary rover which moves across the surface of a planet and conducts a thorough geological study of the celestial surface. This type of rover system is still ad-hoc in that it incorporates its software into its core hardware making the whole system cohesive, tightly-coupled, more susceptible to shortcomings, less flexible, hard to be scaled and maintained, and impossible to be adapted to other purposes. This paper proposes a service-oriented architecture for space exploration robotic rover systems made out of loosely-coupled and distributed web services. The proposed architecture consists of three elementary tiers: the client tier that corresponds to the actual rover; the server tier that corresponds to the web services; and the middleware tier that corresponds to an Enterprise Service Bus which promotes interoperability between the interconnected entities. The niche of this architecture is that rover's software components are decoupled and isolated from the rover's body and possibly deployed at a distant location. A service-oriented architecture promotes integrate-ability, scalability, reusability, maintainability, and interoperability for client-to-server communication.Comment: LACSC - Lebanese Association for Computational Sciences, http://www.lacsc.org/; International Journal of Science & Emerging Technologies (IJSET), Vol. 3, No. 2, February 201

Architectures and Evaluation for Adjustable Control Autonomy for Space-Based Life Support Systems

In the past five years, a number of automation applications for control of crew life support systems have been developed and evaluated in the Adjustable Autonomy Testbed at NASA's Johnson Space Center. This paper surveys progress on an adjustable autonomous control architecture for situations where software and human operators work together to manage anomalies and other system problems. When problems occur, the level of control autonomy can be adjusted, so that operators and software agents can work together on diagnosis and recovery. In 1997 adjustable autonomy software was developed to manage gas transfer and storage in a closed life support test. Four crewmembers lived and worked in a chamber for 91 days, with both air and water recycling. CO2 was converted to O2 by gas processing systems and wheat crops. With the automation software, significantly fewer hours were spent monitoring operations. System-level validation testing of the software by interactive hybrid simulation revealed problems both in software requirements and implementation. Since that time, we have been developing multi-agent approaches for automation software and human operators, to cooperatively control systems and manage problems. Each new capability has been tested and demonstrated in realistic dynamic anomaly scenarios, using the hybrid simulation tool

Onboard Mission Management for a VTOL UAV Using Sequence and Supervisory Control

This chapter addresses the challenges of onboard mission management for small, low flying UAVs in order to reduce their dependency on reliable remote control. The system presented and tested onboard an unmanned aerial vehicle (UAV) provides levels of autonomy, scalable at runtime either by the operator or due to the absence of a data link. This way, it is a feasible approach towards autonomous flight guidance within the low-altitude domain (e.g. urban areas) where unpredictable events are likely to require onboard decision-making. In the following sections the problems of onboard mission management, embedded high level architectures and their implementation issues are discussed. The design of a onboard Mission Management System for a test platform with vertical take-off and landing (VTOL) capabilities is presented, followed by discussions of the implemented system and a research outlook

Distributed control and navigation system for quadrotor UAVs in GPS-denied environments

The problem of developing distributed control and navigation system for quadrotor UAVs operating in GPS-denied environments is addressed in the paper. Cooperative navigation, marker detection and mapping task solved by a team of multiple unmanned aerial vehicles is chosen as demo example. Developed intelligent control system complies with on 4D\RCS reference model and its implementation is based on ROS framework. Custom implementation of EKF-based map building algorithm is used to solve marker detection and map building task.Comment: Camera-ready as submitted (and accepted) to the 7th IEEE International Conference Intelligent Systems IS'2014, September 24-26, 2014, Warsaw, Polan

MERLIN2: MachinEd Ros 2 pLanINg

Permanent link to code/repository used for this code version: https://github.com/SoftwareImpacts/SIMPAC-2023-26[EN] Any service robot should be able to make decisions and schedule tasks to reach predefined goals such as opening a door or assisting users at home. However, these processes are not single short-term tasks anymore and it is required to set long-term skills for establishing a control architecture that allows robots to perform daily tasks. This paper presents MERLIN2, a hybrid cognitive architecture based on symbolic planning and state machine decision-making systems that allows performing robot behaviors. The architecture can run in any robot running ROS 2, the latest version of the Robot Operative System. MERLIN2 is available at https://github.com/MERLIN2-ARCH/merlin2.SIMinisterio de Universidades (FPU21/01438)EUROPEAN REGIONAL DEVELOPMENT FUND (ERDF) "Una manera de hacer Europa

Robotic Architectures

In the development of mobile robotic systems, a robotic architecture plays a crucial role in interconnecting all the sub-systems and controlling the system. The design of robotic architectures for mobile autonomous robots is a challenging and complex task. With a number of existing architectures and tools to choose from, a review of the existing robotic architecture is essential. This paper surveys the different paradigms in robotic architectures. A classification of the existing robotic architectures and comparison of different proposals attributes and properties have been carried out. The paper also provides a view on the current state of designing robot architectures. It also proposes a conceptual model of a generalised robotic architecture for mobile autonomous robots.Defence Science Journal, 2010, 60(1), pp.15-22, DOI:http://dx.doi.org/10.14429/dsj.60.9

Using CONFIG for Simulation of Operation of Water Recovery Subsystems for Advanced Control Software Evaluation

A hybrid discrete/continuous simulation tool, CONFIG, has been developed to support evaluation of the operability life support systems. CON FIG simulates operations scenarios in which flows and pressures change continuously while system reconfigurations occur as discrete events. In simulations, intelligent control software can interact dynamically with hardware system models. CONFIG simulations have been used to evaluate control software and intelligent agents for automating life support systems operations. A CON FIG model of an advanced biological water recovery system has been developed to interact with intelligent control software that is being used in a water system test at NASA Johnson Space Cente