Do. D 2. 01. 7. A STTR Solicitation . These software tools intended for multi- vehicle collaboration compatible with open architectures that adapt to environments in which energy efficiency is of significant importance and communications may be intermittent, low bandwidth, short range, and/or noisy. DESCRIPTION: The last decade has seen substantial growth in the development of cross- domain open robotics architectures and methods for multi- vehicle collaboration. However, many popular multi- vehicle control methods may be somewhat power intensive in the way they solve these problems or at least don't fully take advantage of opportunities to be more efficient collectively; particularly for systems that cannot be centrally controlled due to the severe communications limitations found in many naval mission tasks. PHASE I: Determine feasibility for the development of integrated multi- vehicle planning and autonomous control algorithms that can be used to balance energy efficiency and mission tasks. Phase I will provide initial development of the proposed tools and experimentation using a limited- fidelity simulation or hardware testing, if feasible. Hardware testing is not required for Phase I. Feasibility can be demonstrated through simulation and should include appropriate models of the relevant platform, sensing, communications and the relevant environmental phenomena at a reasonable level of complexity and incorporating uncertainty in the problem to show closed- loop performance, and robustness. For Phase I, while the experimental platform should have representative complexity, it does not necessarily require a high degree of fidelity to particular naval systems or missions. An existing research capability may be used for initial proof of concept. Phase I can consider only a limited set of mission tasks, environmental factors, and platform types with sufficient functionality to demonstrate feasibility, but they would ideally be chosen to demonstrate the broader applicability of the concept. PHASE II: Based on the Phase I effort develop the multi- vehicle planning and autonomous control algorithms tools for a broader set of mission tasks and system types and testing using either higher fidelity nonlinear system models with sufficient complexity for a proof of concept or hardware in- the- loop or flight/in- water testing using inexpensive surrogates. PHASE III: Finalize software development of the multi- vehicle planning and autonomous control algorithms prototype with compatibility to open architectures and address any unique requirements for interoperability with a particular target domain(s), perform a more formal systems integration task to provide effective software interfaces to particular naval assets, perform operational testing, and participate in integrated demonstrations of autonomous systems operations. TECHNOLOGY AREA(S): Sensors. OBJECTIVE: Atomic Layer Deposition (ALD) techniques have established the ability to grow conformal, defect free films over large areas. How to Find The Suitable Size of Cable & Wire for Electrical Wiring Installation (Solved Examples in British and SI System) Electrical Technology 10/18/2013 Basic. REFERENCES: 1. Steinberg, Marc et al, Long duration autonomy for maritime systems: challenges and opportunities, Autonomous Robots, Springer Verlag, July 2. Yu Ru and Sonia Martinez, . Minghui Zhu and Sonia Mart. Liam Paull, Guoquan Huang, Mae Seto, and John Leonard. Communication- Constrained Multi- AUV Cooperative SLAM. In IEEE Intl. Kamra and N. Ayanian, Dynamic Resource Reallocation for Robots on Long Term Deployments, IEEE Conf. Derenick, N. Michael, and V. Energy- aware coverage control with docking for robot teams. In IEEE/RSJ Intl Conf. Intelligent Robots and Systems, pages 3. San Francisco, Sept. Hollinger, S. Yerramalli, S. Mitra, and G. Sukhatme, Distributed Data Fusion for Multirobot Search, IEEE Transactions on Robotics, vol. Feb. Suzuki, and J. Uav consumable replenishment: Design concepts for automated service stations.
Journal of Intelligent and Robotic Systems, 6. C. Belani, and D. A long term vision for long- range ship- free deep ocean operations: Persistent presence through coordination of autonomous surface vehicles and autonomous underwater vehicles. In IEEE/OES Autonomous Underwater Vehicles, pages 1“7, Southampton, Sept. Kularatne, S. Bhattacharya, M. Choudhary, F. Narayanan, M. Stojanovic, and G. Sukhatme, Structured Sparse Methods for Active Ocean Observation Systems with Communication Constraints , IEEE Communications Magazine, vol. November 2. 01. 5. Raposo, and H. Potentially distributable energy: Towards energy autonomy in large population of mobile robots. In Intl Symp. Computational Intelligence in Robotics and Automation, pages 2. Jacksonville, June 2. Schwager, S. Persistent ocean monitoring with underwater gliders: Adapting sampling resolution. Journal of Field Robotics, 2. Schwager, and D. Persistent monitoring of changing environments using a robot with limited range sensing. In IEEE Intl Conf. Robotics and Automation, pages 5. Shanghai, May 2. 01. Stump and N. Multi- robot persistent surveillance planning as a vehicle routing problem. In IEEE Conf. Automation Science and Engineering, pages 5. Trieste, Italy, Aug 2. Mitchell, D., M. Chakraborty, K. Sycara, and N. Michael, 2. Multi- robot Long- Term Persistent Coverage with Fuel Constrained Robots. In Proceedings of IEEE International Conference on Robotics and Automation. Lawrance, R. Fitch, and S. Sukkarieh, 2. 01. Energy- constrained motion planning for information gathering with autonomous aerial soaring. In ICRA, pp. 3. 82. P. Ponnavaikkoy, K. Yassiny, S. K. Wilsony, M. Stojanovicz and J. Holliday, ``Energy Optimization with Delay Constraints in Underwater Acoustic Networks. IEEE Globecom Conference, Atlanta, GA, December 2. Makovkin, D. Langelaan, . Ani Hsieh, V. Kumar, A Framework for Controlling Diversity to Maximize Performance in a Heterogeneous Swarm of Robots, IEEE International Conference on Robotics and Automation (ICRA), 2. KEYWORDS: Autonomy; Planning; Control; Energy Management; Unmanned Air System; Autonomous Undersea Vehicle; Unmanned Sea Surface Vehicle.
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