1,241 research outputs found

    Design and analysis of proximate mechanisms for cooperative transport in real robots

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    This paper describes a set of experiments in which a homogeneous group of real e-puck robots is required to coordinate their actions in order to transport cuboid objects that are too heavy to be moved by single robots. The agents controllers are dynamic neural networks synthesised through evolutionary computation techniques. To run these experiments, we designed, built, and mounted on the robots a new sensor that returns the agent displacement on the x/y plane. In this object transport scenario, this sensor generates useful feedback on the consequences of the robot actions, helping the robots to perceive whether their pushing forces are aligned with the object movement. The results of our experiments indicated that the best evolved controller can effectively operate on real robots. The group transport strategies turned out to be robust and scalable to effectively operate in a variety of conditions in which we vary physical characteristics of the object and group cardinality. From a biological perspective, the results of this study indicate that the perception of the object movement could explain how natural organisms manage to coordinate their actions to transport heavy items

    Autonomous Systems, Robotics, and Computing Systems Capability Roadmap: NRC Dialogue

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    Contents include the following: Introduction. Process, Mission Drivers, Deliverables, and Interfaces. Autonomy. Crew-Centered and Remote Operations. Integrated Systems Health Management. Autonomous Vehicle Control. Autonomous Process Control. Robotics. Robotics for Solar System Exploration. Robotics for Lunar and Planetary Habitation. Robotics for In-Space Operations. Computing Systems. Conclusion

    Linear Time-Varying MPC for Nonprehensile Object Manipulation with a Nonholonomic Mobile Robot

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    This paper proposes a technique to manipulate an object with a nonholonomic mobile robot by pushing, which is a nonprehensile manipulation motion primitive. Such a primitive involves unilateral constraints associated with the friction between the robot and the manipulated object. Violating this constraint produces the slippage of the object during the manipulation, preventing the correct achievement of the task. A linear time-varying model predictive control is designed to include the unilateral constraint within the control action properly. The approach is verified in a dynamic simulation environment through a Pioneer 3-DX wheeled robot executing the pushing manipulation of a package

    Scalable Control Strategies and a Customizable Swarm Robotic Platform for Boundary Coverage and Collective Transport Tasks

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    abstract: Swarms of low-cost, autonomous robots can potentially be used to collectively perform tasks over large domains and long time scales. The design of decentralized, scalable swarm control strategies will enable the development of robotic systems that can execute such tasks with a high degree of parallelism and redundancy, enabling effective operation even in the presence of unknown environmental factors and individual robot failures. Social insect colonies provide a rich source of inspiration for these types of control approaches, since they can perform complex collective tasks under a range of conditions. To validate swarm robotic control strategies, experimental testbeds with large numbers of robots are required; however, existing low-cost robots are specialized and can lack the necessary sensing, navigation, control, and manipulation capabilities. To address these challenges, this thesis presents a formal approach to designing biologically-inspired swarm control strategies for spatially-confined coverage and payload transport tasks, as well as a novel low-cost, customizable robotic platform for testing swarm control approaches. Stochastic control strategies are developed that provably allocate a swarm of robots around the boundaries of multiple regions of interest or payloads to be transported. These strategies account for spatially-dependent effects on the robots' physical distribution and are largely robust to environmental variations. In addition, a control approach based on reinforcement learning is presented for collective payload towing that accommodates robots with heterogeneous maximum speeds. For both types of collective transport tasks, rigorous approaches are developed to identify and translate observed group retrieval behaviors in Novomessor cockerelli ants to swarm robotic control strategies. These strategies can replicate features of ant transport and inherit its properties of robustness to different environments and to varying team compositions. The approaches incorporate dynamical models of the swarm that are amenable to analysis and control techniques, and therefore provide theoretical guarantees on the system's performance. Implementation of these strategies on robotic swarms offers a way for biologists to test hypotheses about the individual-level mechanisms that drive collective behaviors. Finally, this thesis describes Pheeno, a new swarm robotic platform with a three degree-of-freedom manipulator arm, and describes its use in validating a variety of swarm control strategies.Dissertation/ThesisDoctoral Dissertation Mechanical Engineering 201

    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

    Innovative Tokyo

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    This paper compares and contrasts Tokyo's innovation structure with the industrial districts model and the international hub model in the literature on urban and regional development. The Tokyo model embraces and yet transcends both industrial districts and international hub models. The paper details key elements making up the Tokyo model-organizational knowledge creation, integral and co-location systems of corporate R&D and new product development, test markets, industrial districts and clusters, participative consumer culture, continuous learning from abroad, local government policies, the national system of innovation, and the historical genesis of Tokyo in Japan's political economy. The paper finds that the Tokyo model of innovation will continue to evolve with the changing external environment, but fundamentally retains its main characteristics. The lessons from the Tokyo model is that openness, a diversified industrial base, the continuing development of new industries, and an emphasis on innovation, all contribute to the dynamism of a major metropolitan region.Labor Policies,Environmental Economics&Policies,Public Health Promotion,ICT Policy and Strategies,Agricultural Knowledge&Information Systems,ICT Policy and Strategies,Environmental Economics&Policies,Health Monitoring&Evaluation,Agricultural Knowledge&Information Systems,Innovation

    Information Transfer in a Flocking Robot Swarm

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    Natural search algorithms as a bridge between organisms, evolution, and ecology

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    The ability to navigate is a hallmark of living systems, from single cells to higher animals. Searching for targets, such as food or mates in particular, is one of the fundamental navigational tasks many organisms must execute to survive and reprod uce. Here, we argue that a recent surge of studies of the proximate mechanisms that underlie search behavior offers a new opportunity to integrate the biophysics and neuroscience of sensory systems with ecological and evolutionary processes, closing a feedback loop that promises exciting new avenues of scientific exploration at the frontier of systems biology. Keywords: sensing; navigation; evolutionary strategy; encounter rates; exploration–exploitationGordon and Betty Moore Foundation (Award GBMF3783
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