1,440 research outputs found

    Autonomous robot manipulator-based exploration and mapping system for bridge maintenance

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    This paper presents a system for Autonomous eXploration to Build A Map (AXBAM) of an unknown, 3D complex steel bridge structure using a 6 degree-of-freedom anthropomorphic robot manipulator instrumented with a laser range scanner. The proposed algorithm considers the trade-off between the predicted environment information gain available from a sensing viewpoint and the manipulator joint angle changes required to position a sensor at that viewpoint, and then obtains collision-free paths through safe, previously explored regions. Information gathered from multiple viewpoints is fused to achieve a detailed 3D map. Experimental results show that the AXBAM system explores and builds quality maps of complex unknown regions in a consistent and timely manner. © 2011 Elsevier B.V. All rights reserved

    A novel surface segmentation approach for robotic manipulator-based maintenance operation planning

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    This paper presents a novel approach to segmenting a three-dimensional surface map by considering the task requirements and the movements of an industrial robot manipulator. Maintenance operations, such as abrasive blasting, that are performed by a field robot manipulator can be made more efficient by exploiting surface segmentation. The approach in this paper utilises an aggregate of multiple connectivity graphs, with graph edges defined by task constraints, and graph vertices that correspond to small, maintenance-specific target surfaces, known as Scale-Like Discs (SLDs). The task constraints for maintenance operations are based on the characteristics of neighbouring SLDs. The combined connectivity graphs are analysed to find clusters of vertices, thus segmenting the surface map into groups of related SLDs. Experiments conducted in three typical bridge maintenance environments have shown that the approach can reduce garnet usage by 10%-40% and reduce the manipulator joint movements by up to 35%. © 2012 Elsevier B.V. All rights reserved

    A robotic system for steel bridge maintenance: Research challenges and system design

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    This paper presents the research on and development of a robotic system for stripping paint and rust from steel bridges, with the ultimate objective of preventing human exposure to hazardous and dangerous debris (containing rust, paint particles, lead and/or asbestos), relieving human workers from labor intensive tasks and reducing costs associated with bridge maintenance. The robot system design, the key research challenges and enabling technologies and system development are discussed in detail. Research results obtained so far and discussions on some key issues are also presented

    A robotic system for steel bridge maintenance: Field testing

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    This paper presents the field testing results of an autonomous manipulator-based robotic system that strips the paint and rust from steel bridges [Liu et al., 2008]. The key components of this system are sensing and planning, which have been presented in other research papers. The grit-blasting field trial presented in this paper spanned 6 weeks, and included 20 hours over 4.5 days of actual grit-blasting operation. The field testing has verified the algorithms developed for exploration, mapping, surface segmentation, robot motion planning and collision avoidance. It has also proved that the robotic system is able to perform bridge maintenance operations (grit-blasting), reduce human workers' exposure to hazardous and dangerous debris (containing rust, lead-based paint particles), and relieve workers from labour-intensive tasks. The system has been shown to position a grit-blast nozzle so as to remove the paint and rust at the same rate that is expected of a worker with equivalent equipment: small grit-blasting pot and medium-sized hose nozzle. Testing in the field has also highlighted important issues that need to be addressed

    Infrastructure robotics: Research challenges and opportunities

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    Infrastructure robotics is about research on and development of methodologies that enable robotic systems to be used in civil infrastructure inspection, maintenance and rehabilitation. This paper briefly discusses the current research challenges and opportunities in infrastructure robotics, and presents a review of the research activities and projects in this field at the Centre for Autonomous Systems, University of Technology Sydney

    A sliding window approach to exploration for 3D map building using a biologically inspired bridge inspection robot

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    © 2015 IEEE. This paper presents a Sliding Window approach to viewpoint selection when exploring an environment using a RGB-D sensor mounted to the end-effector of an inchworm climbing robot for inspecting areas inside steel bridge archways which cannot be easily accessed by workers. The proposed exploration approach uses a kinematic chain robot model and information theory-based next best view calculations to predict poses which are safe and are able to reduce the information remaining in an environment. At each exploration step, a viewpoint is selected by analysing the Pareto efficiency of the predicted information gain and the required movement for a set of candidate poses. In contrast to previous approaches, a sliding window is used to determine candidate poses so as to avoid the costly operation of assessing the set of candidates in its entirety. Experimental results in simulation and on a prototype climbing robot platform show the approach requires fewer gain calculations and less robot movement, and therefore is more efficient than other approaches when exploring a complex 3D steel bridge structure

    Prior-knowledge assisted fast 3D map building of structured environments for steel bridge maintenance

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    Practical application of a robot in a structured, yet unknown environment, such as in bridge maintenance, requires the robot to quickly generate an accurate map of the surfaces in the environment. A consistent and complete map is fundamental to achieving reliable and robust operation. In a real-world and field application, sensor noise and insufficient exploration oftentimes result in an incomplete map. This paper presents a robust environment mapping approach using prior knowledge in combination with a single depth camera mounted on the end-effector of a robotic manipulator. The approach has been successfully implemented in an industrial setting for the purpose of steel bridge maintenance. A prototype robot, which includes the presented map building approach in its software package, has recently been delivered to industry. © 2013 IEEE

    Remote systems development

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    Potential space missions of the nineties and the next century require that we look at the broad category of remote systems as an important means to achieve cost-effective operations, exploration and colonization objectives. This paper addresses such missions, which can use remote systems technology as the basis for identifying required capabilities which must be provided. The relationship of the space-based tasks to similar tasks required for terrestrial applications is discussed. The development status of the required technology is assessed and major issues which must be addressed to meet future requirements are identified. This includes the proper mix of humans and machines, from pure teleoperation to full autonomy; the degree of worksite compatibility for a robotic system; and the required design parameters, such as degrees-of-freedom. Methods for resolution are discussed including analysis, graphical simulation and the use of laboratory test beds. Grumman experience in the application of these techniques to a variety of design issues are presented utilizing the Telerobotics Development Laboratory which includes a 17-DOF robot system, a variety of sensing elements, Deneb/IRIS graphics workstations and control stations. The use of task/worksite mockups, remote system development test beds and graphical analysis are discussed with examples of typical results such as estimates of task times, task feasibility and resulting recommendations for design changes. The relationship of this experience and lessons-learned to future development of remote systems is also discussed

    Experimental Evaluation of Nearest Neighbor Exploration Approach in Field Environments

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    © 2017 IEEE. Inspecting surface conditions in 3-D environments such as steel bridges is a complex, time-consuming, and often hazardous undertaking that is an essential part of tasks such as bridge maintenance. Developing an autonomous exploration strategy for a mobile climbing robot would allow for such tasks to be completed more quickly and more safely than is possible with human inspectors. The exploration strategy tested in this paper, called the nearest neighbors exploration approach (NNEA), aims to reduce the overall exploration time by reducing the number of sensor position evaluations that need to be performed. NNEA achieves this by first considering at each time step only a small set of poses near to the current robot as candidates for the next best view. This approach is compared with another exploration strategy for similar robots performing the same task. The improvements between the new and previous strategy are demonstrated through trials on a test rig, and also in field trials on a ferromagnetic bridge structure. Note to Practitioners-This paper was motivated by the problem of inspecting confined spaces for rust and flaking paint with a manipulator robot arm. Existing approaches involve creating a large set of candidate robot poses to take a scan from. Evaluating all these candidate poses is very time consuming if full coverage is guaranteed. This paper suggests a principled method for restricting the size of this set in a way that does not reduce inspection coverage but decreases overall time taken for inspection

    An Approach to Base Placement for Effective Collaboration of Multiple Autonomous Industrial Robots

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    There are many benefits for the deployment of multiple autonomous industrial robots to carry out a task, particularly if the robots act in a highly collaborative manner. Collaboration can be possible when each robot is able to autonomously explore the environment, localize itself, create a map of the environment and communicate with other robots. This paper presents an approach to the modeling of the collaboration problem of multiple robots determining optimal base positions and orientations in an environment by considering the team objectives and the information shared amongst the robots. It is assumed that the robots can communicate so as to share information on the environment, their operation status and their capabilities. The approach has been applied to a team of robots that are required to perform complete surface coverage tasks such as grit-blasting and spray painting in unstructured environments. Case studies of such applications are presented to demonstrate the effectiveness of the approach
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