523 research outputs found

    Top-Down & Bottom-Up Approaches to Robot Design

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    This thesis presents a study of different engineering design methodologies and demonstrates their effectiveness and limitations in actual robot designs. Some of these methods were blended together with focus on providing an easily interpreted project design flow while implementing more bottom-up, or feedback, elements into the design methodology. Typically design methods are learned through experience, and design taught in academia aims to shape and formalize previous experience. Usually, inexperienced engineers are taught approaches resembling the Verein Deutscher Ingenieure (VDI) 2221 process. This method presented by the Association of German Engineers in 2006 is regarded as the general system design process. This introductory process is largely left open to interpretation, and it is often unclear when to implement feedback in the design process. The objective of this thesis is to investigate the roles of top-down and bottom-up processes, and how to integrate them in the robot design methodology. The proposed approach utilizes several components from existing design methods. There are three main conditional loops within the proposed approach. The first loop focuses on defining the problem in a top-down manner through logical decomposition, defining technical requirements, researching solutions, and conducting a trade study. These four steps are done iteratively until reaching the bottom of the system, the most primitive components. This is followed by a modeling and analysis loop. This works from the bottom to the top of the design in preparation for manufacturing and validation. The final loop of the proposed approach focuses on validation and verification. The testing and manufacturing involved allows for alterations to the design to fulfill the original technical requirements. These three loops occur until a proof of concept is achieved. The proposed method is intended to be applied iteratively. The first pass of the method results in a proof of concept, while the second results in a preproduction prototype, and the third in a production model. This assembly of design elements provides a project flow that leaves little to be interpreted and is suitable for small design teams while still flexible enough to be applied to diverse robotics projects. This thesis provides three case studies analyzing the application of the hybrid design approach mentioned above to robotic system development. The first study showcases a complicated system design with a small development team. The second case is of simpler construction with a smaller developer team. This simpler case better demonstrates the benefits of this hybrid approach in robotic system development due to the comparatively higher speed at which the system matures. The third case study shows how this same proposed approach can be applied to the design of a bottom-up controlled swarm. These case studies are for future designers to reference as examples of the hybrid design methodology in application, and what can happen when there is a lack of feedback in design. This proposed hybrid design method can encourage design practices in new engineers that translate better to industrial applications, and therefore encourage faster integration of new engineers into established design engineering practices

    Development of Autonomous Optimal Cooperative Control in Relay Rover Configured Small Unmanned Aerial Systems

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    This thesis documents the research effort to develop, integrate and implement the system hardware and the software necessary to validate the Air Force Institute of Technology\u27s theoretical advances in small unmanned aerial systems (SUAS) cooperative control. The end state objective of the research effort was to flight test an autonomous control algorithm on a communication relay unmanned aerial vehicle (UAV) that was actively relaying data to and from a rover UAV. The relay UAV is one part of a SUAS designed to utilize cooperative control to extend the effective line-of-sight operating range for a rover UAV. An algorithm is integrated into ground control software that takes telemetry data (the current position of the ground station, rover UAV, and relay UAV) to determine where to navigate the relay aircraft for optimal communication signal strength. The ground station operator flies the rover aircraft in the extended line-of-sight operational envelope just as she/he would in the normal line-of-sight operations. The relay UAV is autonomously routed to the optimal communications relay position. The research yielded a SUAS based on the Ardupilot Mega 2.0. Flight testing demonstrated the SUAS\u27s ability to generate the correct navigation data autonomously; however, the navigation data was not successfully activated as current waypoints on the relay UAV \u27s autopilot. Software in the loop testing was utilized to verify a solution to activate the navigation data but flight testing was not conducted to verify the simulation results

    An overview of robotics and autonomous systems for harsh environments

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    Across a wide range of industries and applications, robotics and autonomous systems can fulfil the crucial and challenging tasks such as inspection, exploration, monitoring, drilling, sampling and mapping in areas of scientific discovery, disaster prevention, human rescue and infrastructure management, etc. However, in many situations, the associated environment is either too dangerous or inaccessible to humans. Hence, a wide range of robots have been developed and deployed to replace or aid humans in these activities. A look at these harsh environment applications of robotics demonstrate the diversity of technologies developed. This paper reviews some key application areas of robotics that involve interactions with harsh environments (such as search and rescue, space exploration, and deep-sea operations), gives an overview of the developed technologies and provides a discussion of the key trends and future directions common to many of these areas

    Hardware, Software, and Low-Level Control Scheme Development for a Real-Time Autonomous Rover

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    The objective of this research is to develop a low-cost autonomous rover platform for experiments in autonomous navigation. This thesis describes the design, development, and testing of an autonomous rover platform, based on the commercial, off-the-shelf Tamiya TXT-1 radio controlled vehicle. This vehicle is outfitted with an onboard computer based on the Mini-ITX architecture and an array of sensors for localization and obstacle avoidance, and programmed with Matlab/SimulinkRTM Real-Time Workshop (RTW) utilizing the Linux Real-Time Application Interface (RTAI) operating system.;First, a kinematic model is developed and verified for the rover. Then a proportional-integral-derivative (PID) feedback controller is developed for translational and rotational velocity regulation. Finally, a hybrid navigation controller is developed combining a potential field controller and an obstacle avoidance controller for waypoint tracking.;Experiments are performed to verify the functionality of the kinematic model and the PID velocity controller, and to demonstrate the capabilities of the hybrid navigation controller. These experiments prove that the rover is capable of successfully navigating in an unknown indoor environment. Suggestions for future research include the integration of additional sensors for localization and creation of multiple platforms for autonomous coordination experiments

    Auction-based Task Allocation for Safe and Energy Efficient UAS Parcel Transportation

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    In this paper, two greedy auction-based algorithms are proposed for the allocation of heterogeneous tasks to a heterogeneous fleet of UAVs. The tasks set is composed of parcel delivery tasks and charge tasks, the latter to guarantee service persistency. An optimization problem is solved by each agent to determine its bid for each task. When considering delivery tasks, the bidder aims at minimizing the energy consumption, while the minimization of the flight time is adopted for charge tasks bids. The algorithms include a path planner that computes the minimum risk path for each task-UAV bid exploiting a 2D risk map of the operational area, defined in an urban environment. Each solution approach is implemented by means of two auction strategies: single-item and multiple-item. Considerations about complexity and efficiency of the algorithms are drawn from Monte Carlo simulations

    The Underpinnings of Workload in Unmanned Vehicle Systems

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    This paper identifies and characterizes factors that contribute to operator workload in unmanned vehicle systems. Our objective is to provide a basis for developing models of workload for use in design and operation of complex human-machine systems. In 1986, Hart developed a foundational conceptual model of workload, which formed the basis for arguably the most widely used workload measurement techniquethe NASA Task Load Index. Since that time, however, there have been many advances in models and factor identification as well as workload control measures. Additionally, there is a need to further inventory and describe factors that contribute to human workload in light of technological advances, including automation and autonomy. Thus, we propose a conceptual framework for the workload construct and present a taxonomy of factors that can contribute to operator workload. These factors, referred to as workload drivers, are associated with a variety of system elements including the environment, task, equipment and operator. In addition, we discuss how workload moderators, such as automation and interface design, can be manipulated in order to influence operator workload. We contend that workload drivers, workload moderators, and the interactions among drivers and moderators all need to be accounted for when building complex, human-machine systems

    Implementing Cooperative Behavior & Control Using Open Source Technology Across Heterogeneous Vehicles

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    This thesis describes the research effort into implementing cooperative behavior and control across heterogeneous vehicles using low cost off-the-shelf technologies and open source software. Current cooperative behavior and control methods are explored and improved upon to build analysis models. These analysis models characterize ideal factor settings for implementation and establish limits of performance for these low cost approaches to cooperative behavior and control. The research focused on latency and position accuracy as the two measures of performance. Three different ground control station (GCS) software applications and two types of vehicles, rover ground vehicles and aerial multi-rotors, were used in this research. Using optimum factor settings from Design of Experiments (DOE), the multi-rotor following rover vehicle configuration experienced almost twice the latency of other experiments but also the lowest positional error of 0.8 m. Results show that the achieved update frequency of 0.5 Hz or slower would be far too slow for close-formation flight

    Toward a robot swarm protecting a group of migrants

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    Different geopolitical conflicts of recent years have led to mass migration of several civilian populations. These migrations take place in militarized zones, indicating real danger contexts for the populations. Indeed, civilians are increasingly targeted during military assaults. Defense and security needs have increased; therefore, there is a need to prioritize the protection of migrants. Very few or no arrangements are available to manage the scale of displacement and the protection of civilians during migration. In order to increase their security during mass migration in an inhospitable territory, this article proposes an assistive system using a team of mobile robots, labeled a rover swarm that is able to provide safety area around the migrants. We suggest a coordination algorithm including CNN and fuzzy logic that allows the swarm to synchronize their movements and provide better sensor coverage of the environment. Implementation is carried out using on a reduced scale rover to enable evaluation of the functionalities of the suggested software architecture and algorithms. Results bring new perspectives to helping and protecting migrants with a swarm that evolves in a complex and dynamic environment
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