24 research outputs found

    Novel Reconfigurable Delta Robot Dual-Functioning as Adaptive Landing Gear and Manipulator

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    In this work a novel dual-functioning rotorcraft undercarriage is developed. The design is a reconfigurable delta robot which allows for transformation between Adaptive Landing Gear for vertical take-off and landing and 3DOF Aerial Manipulation mode. To reconfigure between operation modes without reaching singularities, a guideline to find a singularity-free geometry is presented. An adaptive landing control was developed and validated on a test-stand. For the 3DOF manipulation of the delta-structure, a third-order smooth trajectory was presented and integrated. The prototype, also depicted in the accompanying video, is then presented in free flight experiments demonstrating the advantages of the dual-functioning system

    Unified Dynamics and Control of a Robot Manipulator Mounted on a VTOL Aircraft Platform

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    An innovative type of mobile manipulator, designated Manipulator on VTOL (Vertical Take-Off and Landing) Aircraft (MOVA), is proposed as a potential candidate for autonomous execution of field work in less-structured indoor and outdoor environments. Practical use of the MOVA system requires a unified controller that addresses the coupled and complex dynamics of the composite system; especially the interaction of the robotic manipulator with the aircraft airframe. Model-based controller design methods require explicit dynamics models of the MOVA system. Preliminary investigation of a two-dimensional MOVA system toward a dynamics model and controller design is presented in preparation for developing the controller of the more complex MOVA system in 3D space. Dynamics of the planar MOVA system are derived using the Lagrangian approach and then transforming the result into a form that facilitates controller design using the concept of a virtual manipulator. A MOVA end-effector trajectory tracking controller was designed with the transformed dynamics equation using the integrator back-stepping control design framework. Validity of the controller is shown via stability analysis, simulation results, and results from a physical test-bed. A systematic approach is illustrated for the derivation of the 3D MOVA system dynamics equations. The resulting dynamics equations are represented abstractly in the standard robot dynamics form and proven to have the skew-symmetric property, which is a useful property for control derivation. An open source Mathematica program was developed to achieve automatic symbolic derivation of the MOVA system dynamics. Accessory tools were also designed to create a tool-chain that starts with an Autodesk Inventor CAD drawing, generates input to the Mathematica program, and then formats the output for direct use in MATLAB and Simulink. A unified nonlinear control algorithm that controls the 3D MOVA system, including both the aircraft and the onboard manipulator, as a single entity was developed to achieve trajectory tracking of the MOVA end-effector position and attitude based on the explicit dynamics equation. Globally Uniformly Ultimately Bounded (GUUB) stability is proven for the controller using Lyapunov-type stability analysis. Physical testing was constructed in order to to demonstrate the performance of the proposed controller on a MOVA system with a two-link onboard manipulator

    Safe and accurate MAV Control, navigation and manipulation

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    This work focuses on the problem of precise, aggressive and safe Micro Aerial Vehicle (MAV) navigation as well as deployment in applications which require physical interaction with the environment. To address these issues, we propose three different MAV model based control algorithms that rely on the concept of receding horizon control. As a starting point, we present a computationally cheap algorithm which utilizes an approximate linear model of the system around hover and is thus maximally accurate for slow reference maneuvers. Aiming at overcoming the limitations of the linear model parameterisation, we present an extension to the first controller which relies on the true nonlinear dynamics of the system. This approach, even though computationally more intense, ensures that the control model is always valid and allows tracking of full state aggressive trajectories. The last controller addresses the topic of aerial manipulation in which the versatility of aerial vehicles is combined with the manipulation capabilities of robotic arms. The proposed method relies on the formulation of a hybrid nonlinear MAV-arm model which also takes into account the effects of contact with the environment. Finally, in order to enable safe operation despite the potential loss of an actuator, we propose a supervisory algorithm which estimates the health status of each motor. We further showcase how this can be used in conjunction with the nonlinear controllers described above for fault tolerant MAV flight. While all the developed algorithms are formulated and tested using our specific MAV platforms (consisting of underactuated hexacopters for the free flight experiments, hexacopter-delta arm system for the manipulation experiments), we further discuss how these can be applied to other underactuated/overactuated MAVs and robotic arm platforms. The same applies to the fault tolerant control where we discuss different stabilisation techniques depending on the capabilities of the available hardware. Even though the primary focus of this work is on feedback control, we thoroughly describe the custom hardware platforms used for the experimental evaluation, the state estimation algorithms which provide the basis for control as well as the parameter identification required for the formulation of the various control models. We showcase all the developed algorithms in experimental scenarios designed to highlight the corresponding strengths and weaknesses as well as show that the proposed methods can run in realtime on commercially available hardware.Open Acces

    UAV or Drones for Remote Sensing Applications in GPS/GNSS Enabled and GPS/GNSS Denied Environments

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    The design of novel UAV systems and the use of UAV platforms integrated with robotic sensing and imaging techniques, as well as the development of processing workflows and the capacity of ultra-high temporal and spatial resolution data, have enabled a rapid uptake of UAVs and drones across several industries and application domains.This book provides a forum for high-quality peer-reviewed papers that broaden awareness and understanding of single- and multiple-UAV developments for remote sensing applications, and associated developments in sensor technology, data processing and communications, and UAV system design and sensing capabilities in GPS-enabled and, more broadly, Global Navigation Satellite System (GNSS)-enabled and GPS/GNSS-denied environments.Contributions include:UAV-based photogrammetry, laser scanning, multispectral imaging, hyperspectral imaging, and thermal imaging;UAV sensor applications; spatial ecology; pest detection; reef; forestry; volcanology; precision agriculture wildlife species tracking; search and rescue; target tracking; atmosphere monitoring; chemical, biological, and natural disaster phenomena; fire prevention, flood prevention; volcanic monitoring; pollution monitoring; microclimates; and land use;Wildlife and target detection and recognition from UAV imagery using deep learning and machine learning techniques;UAV-based change detection

    2020 NASA Technology Taxonomy

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    This document is an update (new photos used) of the PDF version of the 2020 NASA Technology Taxonomy that will be available to download on the OCT Public Website. The updated 2020 NASA Technology Taxonomy, or "technology dictionary", uses a technology discipline based approach that realigns like-technologies independent of their application within the NASA mission portfolio. This tool is meant to serve as a common technology discipline-based communication tool across the agency and with its partners in other government agencies, academia, industry, and across the world

    The use of modern tools for modelling and simulation of UAV with Haptic

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    Unmanned Aerial Vehicle (UAV) is a research field in robotics which is in high demand in recent years, although there still exist many unanswered questions. In contrast, to the human operated aerial vehicles, it is still far less used to the fact that people are dubious about flying in or flying an unmanned vehicle. It is all about giving the control right to the computer (which is the Artificial Intelligence) for making decisions based on the situation like human do but this has not been easy to make people understand that it’s safe and to continue the enhancement on it. These days there are many types of UAVs available in the market for consumer use, for applications like photography to play games, to map routes, to monitor buildings, for security purposes and much more. Plus, these UAVs are also being widely used by the military for surveillance and for security reasons. One of the most commonly used consumer product is a quadcopter or quadrotor. The research carried out used modern tools (i.e., SolidWorks, Java Net Beans and MATLAB/Simulink) to model controls system for Quadcopter UAV with haptic control system to control the quadcopter in a virtual simulation environment and in real time environment. A mathematical model for the controlling the quadcopter in simulations and real time environments were introduced. Where, the design methodology for the quadcopter was defined. This methodology was then enhanced to develop a virtual simulation and real time environments for simulations and experiments. Furthermore, the haptic control was then implemented with designed control system to control the quadcopter in virtual simulation and real time experiments. By using the mathematical model of quadcopter, PID & PD control techniques were used to model the control setup for the quadcopter altitude and motion controls as work progressed. Firstly, the dynamic model is developed using a simple set of equations which evolves further by using complex control & mathematical model with precise function of actuators and aerodynamic coefficients Figure5-7. The presented results are satisfying and shows that flight experiments and simulations of the quadcopter control using haptics is a novel area of research which helps perform operations more successfully and give more control to the operator when operating in difficult environments. By using haptic accidents can be minimised and the functional performance of the operator and the UAV will be significantly enhanced. This concept and area of research of haptic control can be further developed accordingly to the needs of specific applications

    The use of modern tools for modelling and simulation of UAV with Haptic

    Get PDF
    Unmanned Aerial Vehicle (UAV) is a research field in robotics which is in high demand in recent years, although there still exist many unanswered questions. In contrast, to the human operated aerial vehicles, it is still far less used to the fact that people are dubious about flying in or flying an unmanned vehicle. It is all about giving the control right to the computer (which is the Artificial Intelligence) for making decisions based on the situation like human do but this has not been easy to make people understand that it’s safe and to continue the enhancement on it. These days there are many types of UAVs available in the market for consumer use, for applications like photography to play games, to map routes, to monitor buildings, for security purposes and much more. Plus, these UAVs are also being widely used by the military for surveillance and for security reasons. One of the most commonly used consumer product is a quadcopter or quadrotor. The research carried out used modern tools (i.e., SolidWorks, Java Net Beans and MATLAB/Simulink) to model controls system for Quadcopter UAV with haptic control system to control the quadcopter in a virtual simulation environment and in real time environment. A mathematical model for the controlling the quadcopter in simulations and real time environments were introduced. Where, the design methodology for the quadcopter was defined. This methodology was then enhanced to develop a virtual simulation and real time environments for simulations and experiments. Furthermore, the haptic control was then implemented with designed control system to control the quadcopter in virtual simulation and real time experiments. By using the mathematical model of quadcopter, PID & PD control techniques were used to model the control setup for the quadcopter altitude and motion controls as work progressed. Firstly, the dynamic model is developed using a simple set of equations which evolves further by using complex control & mathematical model with precise function of actuators and aerodynamic coefficients Figure5-7. The presented results are satisfying and shows that flight experiments and simulations of the quadcopter control using haptics is a novel area of research which helps perform operations more successfully and give more control to the operator when operating in difficult environments. By using haptic accidents can be minimised and the functional performance of the operator and the UAV will be significantly enhanced. This concept and area of research of haptic control can be further developed accordingly to the needs of specific applications

    Informed Data Selection For Dynamic Multi-Camera Clusters

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    Traditional multi-camera systems require a fixed calibration between cameras to provide the solution at the correct scale, which places many limitations on its performance. This thesis investigates the calibration of dynamic camera clusters, or DCCs, where one or more of the cluster cameras is mounted to an actuated mechanism, such as a gimbal or robotic manipulator. Our novel calibration approach parameterizes the actuated mechanism using the Denavit-Hartenberg convention, then determines the calibration parameters which allow for the estimation of the time varying extrinsic transformations between the static and dynamic camera frames. A degeneracy analysis is also presented, which identifies redundant parameters of the DCC calibration system. In order to automate the calibration process, this thesis also presents two information theoretic methods which selects the optimal calibration viewpoints using a next-best-view strategy. The first strategy looks at minimizing the entropy of the calibration parameters, while the second method selects the viewpoints which maximize the mutual information between the joint angle input and calibration parameters. Finally, the effective selection of key-frames is also an essential aspect of robust visual navigation algorithms, as it ensures metrically consistent mapping solutions while reducing the computational complexity of the bundle adjustment process. To that end, we propose two entropy based methods which aim to insert key-frames that will directly improve the system's ability to localize. The first approach inserts key-frames based on the cumulative point entropy reduction in the existing map, while the second approach uses the predicted point flow discrepancy to select key-frames which best initialize new features for the camera to track against in the future. The DCC calibration methods are verified in both simulation and using physical hardware consisting of a 5-DOF Fanuc manipulator and a 3-DOF Aeryon Skyranger gimbal. We demonstrate that the proposed methods are able to achieve high quality calibrations using RMSE pixel error metrics, as well as through analysis of the estimator covariance matrix. The key-frame insertion methods are implemented within the Multi-Camera Parallel Mapping and Tracking (MCPTAM) framework, and we confirm the effectiveness of these approaches using high quality ground truth collected using an indoor positioning system

    Climbing and Walking Robots

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    Nowadays robotics is one of the most dynamic fields of scientific researches. The shift of robotics researches from manufacturing to services applications is clear. During the last decades interest in studying climbing and walking robots has been increased. This increasing interest has been in many areas that most important ones of them are: mechanics, electronics, medical engineering, cybernetics, controls, and computers. Today’s climbing and walking robots are a combination of manipulative, perceptive, communicative, and cognitive abilities and they are capable of performing many tasks in industrial and non- industrial environments. Surveillance, planetary exploration, emergence rescue operations, reconnaissance, petrochemical applications, construction, entertainment, personal services, intervention in severe environments, transportation, medical and etc are some applications from a very diverse application fields of climbing and walking robots. By great progress in this area of robotics it is anticipated that next generation climbing and walking robots will enhance lives and will change the way the human works, thinks and makes decisions. This book presents the state of the art achievments, recent developments, applications and future challenges of climbing and walking robots. These are presented in 24 chapters by authors throughtot the world The book serves as a reference especially for the researchers who are interested in mobile robots. It also is useful for industrial engineers and graduate students in advanced study

    Multi-Robot Systems: Challenges, Trends and Applications

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    This book is a printed edition of the Special Issue entitled “Multi-Robot Systems: Challenges, Trends, and Applications” that was published in Applied Sciences. This Special Issue collected seventeen high-quality papers that discuss the main challenges of multi-robot systems, present the trends to address these issues, and report various relevant applications. Some of the topics addressed by these papers are robot swarms, mission planning, robot teaming, machine learning, immersive technologies, search and rescue, and social robotics
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