353 research outputs found

    Haptic Tele-operation of Wheeled Mobile Robot and Unmanned Aerial Vehicle over the Internet

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    Teleoperation of ground/aerial vehicle extends operator\u27s ability (e.g. expertise, strength, mobility) into the remote environment, and haptic feedback enhances the human operator\u27s perception of the slave environment. In my thesis, two cases are studied: wheeled mobile robot (MWR) haptic tele-driving over the Internet and unmanned aerial vehicle (UAV) haptic teleoperation over the Internet. We propose novel control frameworks for both dynamic WMR and kinematic WMR in various tele-driving modes, and for a mixed UAV with translational dynamics and attitude kinematics. The recently proposed passive set-position modulation (PSPM) framework is extended to guarantee the passivity and/or stability of the closed-loop system with time-varying/packet-loss in the communication; and proved performance in steady state is shown by theoretical measurements.For UAV teleoperation, we also derive a backstepping trajectory tracking control with robustness analysis. Experimental results for dynamic/kinematic WMR and an indoor quadrotor-type UAV are presented to show the efficacy of the proposed control framework

    Design and modeling of a stair climber smart mobile robot (MSRox)

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    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

    Haptic Feedback Effects on Human Control of a UAV in a Remote Teleoperation Flight Task

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    The remote manual teleoperation of an unmanned aerial vehicle (UAV) by a human operator creates a human-in-the loop system that is of great concern. In a remote teleoperation task, a human pilot must make control decisions based upon sensory information provided by the governed system. Often, this information consists of limited visual feedback provided by onboard cameras that do not provide an operator with an accurate portrayal of their immediate surroundings compromising the safety of the mobile robot. Due to this shortfall, haptic force feedback is often provided to the human in an effort to increase their perceptual awareness of the surrounding world. To investigate the effects of this additional sensory information provided to the human op-erator, we consider two haptic force feedback strategies. They were designed to provide either an attractive force to influence control behavior towards a reference trajectory along a flight path, or a repulsive force directing operators away from obstacles to prevent collision. Subject tests were con-ducted where human operators manually operated a remote UAV through a corridor environment under the conditions of the two strategies. For comparison, the conditions of no haptic feedback and the liner combination of both attractive and repulsive strategies were included in the study. Experi-mental results dictate that haptic force feedback in general (including both attractive and repulsive force feedback) improves the average distance from surrounding obstacles up to 21%. Further statis-tical comparison of repulsive and attractive feedback modalities reveal that even though a repulsive strategy is based directly on obstacles, an attractive strategy towards a reference trajectory is more suitable across all performance metrics. To further examine the effects of haptic aides in a UAV teleoperation task, the behavior of the human system as part of the control loop was also investigated. Through a novel device placed on the end effector of the haptic device, human-haptic interaction forces were captured and further analyzed. With this information, system identification techniques were carried out to determine the plausibility of deriving a human control model for the system. By defining lateral motion as a one-dimensional compensatory tracking task the results show that general human control behavior can be identified where lead compensation in invoked to counteract second-order UAV dynamics

    Skill-based human-robot cooperation in tele-operated path tracking

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    This work proposes a shared-control tele-operation framework that adapts its cooperative properties to the estimated skill level of the operator. It is hypothesized that different aspects of an operatorâ\u80\u99s performance in executing a tele-operated path tracking task can be assessed through conventional machine learning methods using motion-based and task-related features. To identify performance measures that capture motor skills linked to the studied task, an experiment is conducted where users new to tele-operation, practice towards motor skill proficiency in 7 training sessions. A set of classifiers are then learned from the acquired data and selected features, which can generate a skill profile that comprises estimations of userâ\u80\u99s various competences. Skill profiles are exploited to modify the behavior of the assistive robotic system accordingly with the objective of enhancing user experience by preventing unnecessary restriction for skilled users. A second experiment is implemented in which novice and expert users execute the path tracking on different pathways while being assisted by the robot according to their estimated skill profiles. Results validate the skill estimation method and hint at feasibility of shared-control customization in tele-operated path tracking

    Mobile-manipulating UAVs for Sensor Installation, Bridge Inspection and Maintenance

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    A parallel mechanism and smart gripper was designed and mounted on a rotorcraft drone to act as a robotic arm and hand. This empowers the drone to perform aerial manipulation and execute bridge maintenance. Hosing, drilling, and epoxying serve as case studies to test-and-evaluation and verify-and-validate the design. The approach, tasks, and findings are presented and show that the case studies are realizable. Conclusions and recommendations point to employing haptics-based human-in-the-loop approaches that can increase the scope of repair work involved in bridge maintenance

    Command and Control Systems for Search and Rescue Robots

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    The novel application of unmanned systems in the domain of humanitarian Search and Rescue (SAR) operations has created a need to develop specific multi-Robot Command and Control (RC2) systems. This societal application of robotics requires human-robot interfaces for controlling a large fleet of heterogeneous robots deployed in multiple domains of operation (ground, aerial and marine). This chapter provides an overview of the Command, Control and Intelligence (C2I) system developed within the scope of Integrated Components for Assisted Rescue and Unmanned Search operations (ICARUS). The life cycle of the system begins with a description of use cases and the deployment scenarios in collaboration with SAR teams as end-users. This is followed by an illustration of the system design and architecture, core technologies used in implementing the C2I, iterative integration phases with field deployments for evaluating and improving the system. The main subcomponents consist of a central Mission Planning and Coordination System (MPCS), field Robot Command and Control (RC2) subsystems with a portable force-feedback exoskeleton interface for robot arm tele-manipulation and field mobile devices. The distribution of these C2I subsystems with their communication links for unmanned SAR operations is described in detail. Field demonstrations of the C2I system with SAR personnel assisted by unmanned systems provide an outlook for implementing such systems into mainstream SAR operations in the future
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