273 research outputs found

    Using a simple expert system to assist a powered wheelchair user

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    A simple expert system is described that helps wheelchair users to drive their wheelchairs. The expert system takes data in from sensors and a joystick, identifies obstacles and then recommends a safe route. Wheelchair users were timed while driving around a variety of routes and using a joystick controlling their wheelchair via the simple expert system. Ultrasonic sensors are used to detect the obstacles. The simple expert system performed better than other recently published systems. In more difficult situations, wheelchair drivers did better when there was help from a sensor system. Wheelchair users completed routes with the sensors and expert system and results are compared with the same users driving without any assistance. The new systems show a significant improvement

    Development and evaluation of mixed reality-enhanced robotic systems for intuitive tele-manipulation and telemanufacturing tasks in hazardous conditions

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    In recent years, with the rapid development of space exploration, deep-sea discovery, nuclear rehabilitation and management, and robotic-assisted medical devices, there is an urgent need for humans to interactively control robotic systems to perform increasingly precise remote operations. The value of medical telerobotic applications during the recent coronavirus pandemic has also been demonstrated and will grow in the future. This thesis investigates novel approaches to the development and evaluation of a mixed reality-enhanced telerobotic platform for intuitive remote teleoperation applications in dangerous and difficult working conditions, such as contaminated sites and undersea or extreme welding scenarios. This research aims to remove human workers from the harmful working environments by equipping complex robotic systems with human intelligence and command/control via intuitive and natural human-robot- interaction, including the implementation of MR techniques to improve the user's situational awareness, depth perception, and spatial cognition, which are fundamental to effective and efficient teleoperation. The proposed robotic mobile manipulation platform consists of a UR5 industrial manipulator, 3D-printed parallel gripper, and customized mobile base, which is envisaged to be controlled by non-skilled operators who are physically separated from the robot working space through an MR-based vision/motion mapping approach. The platform development process involved CAD/CAE/CAM and rapid prototyping techniques, such as 3D printing and laser cutting. Robot Operating System (ROS) and Unity 3D are employed in the developing process to enable the embedded system to intuitively control the robotic system and ensure the implementation of immersive and natural human-robot interactive teleoperation. This research presents an integrated motion/vision retargeting scheme based on a mixed reality subspace approach for intuitive and immersive telemanipulation. An imitation-based velocity- centric motion mapping is implemented via the MR subspace to accurately track operator hand movements for robot motion control, and enables spatial velocity-based control of the robot tool center point (TCP). The proposed system allows precise manipulation of end-effector position and orientation to readily adjust the corresponding velocity of maneuvering. A mixed reality-based multi-view merging framework for immersive and intuitive telemanipulation of a complex mobile manipulator with integrated 3D/2D vision is presented. The proposed 3D immersive telerobotic schemes provide the users with depth perception through the merging of multiple 3D/2D views of the remote environment via MR subspace. The mobile manipulator platform can be effectively controlled by non-skilled operators who are physically separated from the robot working space through a velocity-based imitative motion mapping approach. Finally, this thesis presents an integrated mixed reality and haptic feedback scheme for intuitive and immersive teleoperation of robotic welding systems. By incorporating MR technology, the user is fully immersed in a virtual operating space augmented by real-time visual feedback from the robot working space. The proposed mixed reality virtual fixture integration approach implements hybrid haptic constraints to guide the operator’s hand movements following the conical guidance to effectively align the welding torch for welding and constrain the welding operation within a collision-free area. Overall, this thesis presents a complete tele-robotic application space technology using mixed reality and immersive elements to effectively translate the operator into the robot’s space in an intuitive and natural manner. The results are thus a step forward in cost-effective and computationally effective human-robot interaction research and technologies. The system presented is readily extensible to a range of potential applications beyond the robotic tele- welding and tele-manipulation tasks used to demonstrate, optimise, and prove the concepts

    Deep Learning architecture to assist with steering a powered wheelchair

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    Space Science Opportunities Augmented by Exploration Telepresence

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    Since the end of the Apollo missions to the lunar surface in December 1972, humanity has exclusively conducted scientific studies on distant planetary surfaces using teleprogrammed robots. Operations and science return for all of these missions are constrained by two issues related to the great distances between terrestrial scientists and their exploration targets: high communication latencies and limited data bandwidth. Despite the proven successes of in-situ science being conducted using teleprogrammed robotic assets such as Spirit, Opportunity, and Curiosity rovers on the surface of Mars, future planetary field research may substantially overcome latency and bandwidth constraints by employing a variety of alternative strategies that could involve: 1) placing scientists/astronauts directly on planetary surfaces, as was done in the Apollo era; 2) developing fully autonomous robotic systems capable of conducting in-situ field science research; or 3) teleoperation of robotic assets by humans sufficiently proximal to the exploration targets to drastically reduce latencies and significantly increase bandwidth, thereby achieving effective human telepresence. This third strategy has been the focus of experts in telerobotics, telepresence, planetary science, and human spaceflight during two workshops held from October 3–7, 2016, and July 7–13, 2017, at the Keck Institute for Space Studies (KISS). Based on findings from these workshops, this document describes the conceptual and practical foundations of low-latency telepresence (LLT), opportunities for using derivative approaches for scientific exploration of planetary surfaces, and circumstances under which employing telepresence would be especially productive for planetary science. An important finding of these workshops is the conclusion that there has been limited study of the advantages of planetary science via LLT. A major recommendation from these workshops is that space agencies such as NASA should substantially increase science return with greater investments in this promising strategy for human conduct at distant exploration sites

    Space Science Opportunities Augmented by Exploration Telepresence

    Get PDF
    Since the end of the Apollo missions to the lunar surface in December 1972, humanity has exclusively conducted scientific studies on distant planetary surfaces using teleprogrammed robots. Operations and science return for all of these missions are constrained by two issues related to the great distances between terrestrial scientists and their exploration targets: high communication latencies and limited data bandwidth. Despite the proven successes of in-situ science being conducted using teleprogrammed robotic assets such as Spirit, Opportunity, and Curiosity rovers on the surface of Mars, future planetary field research may substantially overcome latency and bandwidth constraints by employing a variety of alternative strategies that could involve: 1) placing scientists/astronauts directly on planetary surfaces, as was done in the Apollo era; 2) developing fully autonomous robotic systems capable of conducting in-situ field science research; or 3) teleoperation of robotic assets by humans sufficiently proximal to the exploration targets to drastically reduce latencies and significantly increase bandwidth, thereby achieving effective human telepresence. This third strategy has been the focus of experts in telerobotics, telepresence, planetary science, and human spaceflight during two workshops held from October 3–7, 2016, and July 7–13, 2017, at the Keck Institute for Space Studies (KISS). Based on findings from these workshops, this document describes the conceptual and practical foundations of low-latency telepresence (LLT), opportunities for using derivative approaches for scientific exploration of planetary surfaces, and circumstances under which employing telepresence would be especially productive for planetary science. An important finding of these workshops is the conclusion that there has been limited study of the advantages of planetary science via LLT. A major recommendation from these workshops is that space agencies such as NASA should substantially increase science return with greater investments in this promising strategy for human conduct at distant exploration sites

    Acceptance Testing and Energy-based Mission Reliability in Unmanned Ground Vehicles.

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    The objective of this research is to explore and develop new methodologies and techniques to improve UGV mission reliability. This dissertation focuses on two research issues that are critical in the following UGV deployment phases: (1) prior to field deployment to remove design deficiencies; and (2) during field usage to prevent mission failures. Four specific research topics are accomplished. The first topic focuses on simulation-based acceptance testing. A general framework is proposed to integrate dynamic and static simulations. Statistical hypothesis testing is used to compare static and dynamic simulations to determine when a simple static simulation can be used to replace the complex dynamic simulation. Results show that the static simulation can be used when a failure mechanism is not significantly affected by the dynamic characteristics of the vehicle. The remaining research topics aim at prevention of operational failures due to unexpected energy depletion. A model-based Bayesian prediction framework integrated with a dynamic vehicle model is proposed in the second research topic, which improves traditional approaches for estimation and prediction. The Bayesian framework combines mission prior knowledge with real-time measurements for adaptive prediction of end-of-mission energy requirement. Experimental studies were conducted, which validated and demonstrated the advantages of the framework on roads with different surface types and grades. The third research topic, entitled real-time energy reliable path planning, builds upon the above mentioned prediction framework to identify the most energy reliable path in a stochastic network with unknown and correlated arc lengths. Since traditional sequential optimization techniques cannot be directly applied to this problem, a heuristic approach based on two stage exploration/exploitation is proposed to identify the most reliable path. The framework, which minimizes the cost of exploration, outperforms traditional path planning approaches. In the final research topic, the impact of operator driving style on mission energy requirements is investigated using statistical response surface. While the previous topics help with overall mission planning regardless of the operator’s driving style, here, improving the driving style to increase energy availability is studied. The optimal drive cycle that minimizes energy consumption and procedures for reduction of energy consumption are proposed.PhDIndustrial & Operations EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/107075/1/sadrpour_1.pd
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