307 research outputs found

    Using a Multiobjective Approach to Balance Mission and Network Goals within a Delay Tolerant Network Topology

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    This thesis investigates how to incorporate aspects of an Air Tasking Order (ATO), a Communications Tasking Order (CTO), and a Network Tasking Order (NTO) within a cognitive network framework. This was done in an effort to aid the commander and or network operator by providing automation for battlespace management to improve response time and potential inconsistent problem resolution. In particular, autonomous weapon systems such as unmanned aerial vehicles (UAVs) were the focus of this research This work implemented a simple cognitive process by incorporating aspects of behavior based robotic control principles to solve the multi-objective optimization problem of balancing both network and mission goals. The cognitive process consisted of both a multi-move look ahead component, in which the future outcomes of decisions were estimated, and a subsumption decision making architecture in which these decision-outcome pairs were selected so they co-optimized the dual goals. This was tested within a novel Air force mission scenario consisting of a UAV surveillance mission within a delay tolerant network (DTN) topology. This scenario used a team of small scale UAVs (operating as a team but each running the cognitive process independently) to balance the mission goal of maintaining maximum overall UAV time-on-target and the network goal of minimizing the packet end-to-end delays experienced within the DTN. The testing was accomplished within a MATLAB discrete event simulation. The results indicated that this proposed approach could successfully simultaneously improve both goals as the network goal improved 52% and the mission goal improved by approximately 6%

    Unified Behavior Framework for Reactive Robot Control

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    Behavior-based systems form the basis of autonomous control for many robots. In this article, we demonstrate that a single software framework can be used to represent many existing behavior based approaches. The unified behavior framework presented, incorporates the critical ideas and concepts of the existing reactive controllers. Additionally, the modular design of the behavior framework: (1) simplifies development and testing; (2) promotes the reuse of code; (3) supports designs that scale easily into large hierarchies while restricting code complexity; and (4) allows the behavior based system developer the freedom to use the behavior system they feel will function the best. When a hybrid or three layer control architecture includes the unified behavior framework, a common interface is shared by all behaviors, leaving the higher order planning and sequencing elements free to interchange behaviors during execution to achieve high level goals and plans. The framework\u27s ability to compose structures from independent elements encourages experimentation and reuse while isolating the scope of troubleshooting to the behavior composition. The ability to use elemental components to build and evaluate behavior structures is demonstrated using the Robocode simulation environment. Additionally, the ability of a reactive controller to change its active behavior during execution is shown in a goal seeking robot implementation

    Dynamic networks for robotic control and behaviour selection in interactive environments

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    Traditional robotics have the capabilities of the robot hard coded and have the robot function in structured environments (structured environments are those that are predefined for a given task). This approach can limit the functionality of a robot and how they can interact in an environment. Behaviour networks are reactive systems that are able to function in unstructured dynamic environments by selecting behaviours to execute based on the current state of the environment. Behaviour networks are made up of nodes that represent behaviours and these store an activation value to represent the motivation for that behaviour. The nodes receive inputs from a variety of sources and pass proportions of that input to other nodes in the network.Behaviour networks traditionally also have their capabilities predefined. The main aim of this thesis is to expand upon the concepts of traditional robotics by demonstrating the use of distributed behaviours in an environment. This thesis aims to show that distributing object specific data, such as; behaviours and goals, will assist in the task planning for a mobile robot.This thesis explores and tests the traditional behaviour network with a variety of experiments. Each experiment showcases particular features of the behaviour network including flaws that have been identified. Proposed solutions to the found flaws are then presented and explored. The behaviour network is then tested in a simulated environment with distributed behaviours and the dynamic behaviour network is defined. The thesis demonstrates that distributed behaviours can expand the capabilities of a mobile robot using a dynamic behaviour network

    Overcoming barriers and increasing independence: service robots for elderly and disabled people

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    This paper discusses the potential for service robots to overcome barriers and increase independence of elderly and disabled people. It includes a brief overview of the existing uses of service robots by disabled and elderly people and advances in technology which will make new uses possible and provides suggestions for some of these new applications. The paper also considers the design and other conditions to be met for user acceptance. It also discusses the complementarity of assistive service robots and personal assistance and considers the types of applications and users for which service robots are and are not suitable

    Behavior Flexibility for Autonomous Unmanned Aerial Systems

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    Autonomous unmanned aerial systems (UAS) could supplement and eventually subsume a substantial portion of the mission set currently executed by remote pilots, making UAS more robust, responsive, and numerous than permitted by teleoperation alone. Unfortunately, the development of robust autonomous systems is difficult, costly, and time-consuming. Furthermore, the resulting systems often make little reuse of proven software components and offer limited adaptability for new tasks. This work presents a development platform for UAS which promotes behavioral flexibility. The platform incorporates the Unified Behavior Framework (a modular, extensible autonomy framework), the Robotic Operating System (a RSF), and PX4 (an open- source flight controller). Simulation of UBF agents identify a combination of reactive robotic control strategies effective for small-scale navigation tasks by a UAS in the presence of obstacles. Finally, flight tests provide a partial validation of the simulated results. The development platform presented in this work offers robust and responsive behavioral flexibility for UAS agents in simulation and reality. This work lays the foundation for further development of a unified autonomous UAS platform supporting advanced planning algorithms and inter-agent communication by providing a behavior-flexible framework in which to implement, execute, extend, and reuse behaviors

    OpenSwarm: an event-driven embedded operating system for miniature robots

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    This paper presents OpenSwarm, a lightweight easy-to-use open-source operating system. To our knowledge, it is the first operating system designed for and deployed on miniature robots. OpenSwarm operates directly on a robot’s microcontroller. It has a memory footprint of 1 kB RAM and 12 kB ROM. OpenSwarm enables a robot to execute multiple processes simultaneously. It provides a hybrid kernel that natively supports preemptive and cooperative scheduling, making it suitable for both computationally intensive and swiftly responsive robotics tasks. OpenSwarm provides hardware abstractions to rapidly develop and test platformindependent code. We show how OpenSwarm can be used to solve a canonical problem in swarm robotics—clustering a collection of dispersed objects. We report experiments, conducted with five e-puck mobile robots, that show that an OpenSwarm implementation performs as good as a hardware-near implementation. The primary goal of OpenSwarm is to make robots with severely constrained hardware more accessible, which may help such systems to be deployed in real-world applications

    Multi-Agent Task Allocation for Robot Soccer

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    This is the published version. Copyright De GruyterThis paper models and analyzes task allocation methodologies for multiagent systems. The evaluation process was implemented as a collection of simulated soccer matches. A soccer-simulation software package was used as the test-bed as it provided the necessary features for implementing and testing the methodologies. The methodologies were tested through competitions with a number of available soccer strategies. Soccer game scores, communication, robustness, fault-tolerance, and replanning capabilities were the parameters used as the evaluation criteria for the mul1i-agent systems

    Multi-Robot Task Allocation: A Spatial Queuing Approach

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    Multi-Robot Task Allocation (MRTA) is an important area of research in autonomous multi-robot systems. The main problem in MRTA is to match a set of robots to a set of tasks so that the tasks can be completed by the robots while optimizing a certain metric such as the time required to complete all tasks, distance traveled by the robots and energy expended by the robots. We consider a scenario where the tasks can appear dynamically and the location of tasks are not known a priori by the robots. Additionally, for a task to be completed, it needs to be performed by multiple robots. This setting is called the MR-ST-TA (multi-robot, single-task, time- extended assginment) category of MRTA; solving the MRTA problem for this category is a known NP-hard problem. In this thesis, we address this problem by proposing a new algorithm that uses a spatial queue-based model to allocate tasks between robots while comparing its performance to several other known methods. We have implemented these algorithms on an accurately simulated model of Corobot robots within the Webots simulator for diïŹ€erent numbers of robots and tasks. The results show that our method is adept in all proïŹ€ered environments, especially scenarios that beneïŹt from path planning, whereas other methods display inherent weakness at one end of the spectrum: a decentralized greedy approach exhibits ineïŹƒcient behavior as the robot to task ratio dips below one, whereas the Hungarian method (an oïŹ„ine algorithm) fails to keep pace as the robot count increases

    A non-holonomic, highly human-in-the-loop compatible, assistive mobile robotic platform guidance navigation and control strategy

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    The provision of assistive mobile robotics for empowering and providing independence to the infirm, disabled and elderly in society has been the subject of much research. The issue of providing navigation and control assistance to users, enabling them to drive their powered wheelchairs effectively, can be complex and wide-ranging; some users fatigue quickly and can find that they are unable to operate the controls safely, others may have brain injury re-sulting in periodic hand tremors, quadriplegics may use a straw-like switch in their mouth to provide a digital control signal. Advances in autonomous robotics have led to the development of smart wheelchair systems which have attempted to address these issues; however the autonomous approach has, ac-cording to research, not been successful; users reporting that they want to be active drivers and not passengers. Recent methodologies have been to use collaborative or shared control which aims to predict or anticipate the need for the system to take over control when some pre-decided threshold has been met, yet these approaches still take away control from the us-er. This removal of human supervision and control by an autonomous system makes the re-sponsibility for accidents seriously problematic. This thesis introduces a new human-in-the-loop control structure with real-time assistive lev-els. One of these levels offers improved dynamic modelling and three of these levels offer unique and novel real-time solutions for: collision avoidance, localisation and waypoint iden-tification, and assistive trajectory generation. This architecture and these assistive functions always allow the user to remain fully in control of any motion of the powered wheelchair, shown in a series of experiments
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