Mechanical Engineering Research Works
Permanent URI for this collectionhttp://hdl.handle.net/1903/1661
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Item Multipass Target Search in Natural Environments(MDPI, 2017-11-02) Kuhlman, Michael J.; Otte, Michael W.; Sofge, Donald; Gupta, Satyandra K.Consider a disaster scenario where search and rescue workers must search difficult to access buildings during an earthquake or flood. Often, finding survivors a few hours sooner results in a dramatic increase in saved lives, suggesting the use of drones for expedient rescue operations. Entropy can be used to quantify the generation and resolution of uncertainty. When searching for targets, maximizing mutual information of future sensor observations will minimize expected target location uncertainty by minimizing the entropy of the future estimate. Motion planning for multi-target autonomous search requires planning over an area with an imperfect sensor and may require multiple passes, which is hindered by the submodularity property of mutual information. Further, mission duration constraints must be handled accordingly, requiring consideration of the vehicle’s dynamics to generate feasible trajectories and must plan trajectories spanning the entire mission duration, something which most information gathering algorithms are incapable of doing. If unanticipated changes occur in an uncertain environment, new plans must be generated quickly. In addition, planning multipass trajectories requires evaluating path dependent rewards, requiring planning in the space of all previously selected actions, compounding the problem. We present an anytime algorithm for autonomous multipass target search in natural environments. The algorithm is capable of generating long duration dynamically feasible multipass coverage plans that maximize mutual information using a variety of techniques such as 𝜖-admissible heuristics to speed up the search. To the authors’ knowledge this is the first attempt at efficiently solving multipass target search problems of such long duration. The proposed algorithm is based on best first branch and bound and is benchmarked against state of the art algorithms adapted to the problem in natural Simplex environments, gathering the most information in the given search time.Item A design framework for realizing multifunctional wings for flapping wing air vehicles using solar cells(SAGE Publications, 2019-04-10) Holness, Alex E.; Solheim, Hannah; Bruck, Hugh A.; Gupta, Satyandra K.Long flight durations are highly desirable to expand mission capabilities for unmanned air systems and autonomous applications in particular. Flapping wing aerial vehicles are unmanned air system platforms offering several performance advantages over fixed wing and rotorcraft platforms, but are unable to reach comparable flight times when powered by batteries. One solution to this problem has been to integrate energy harvesting technologies in components, such as wings. To this end, a framework for designing flapping wing aerial vehicle using multifunctional wings using solar cells is described. This framework consists of: (1) modeling solar energy harvesting while flying, (2) determining the number of solar cells that meet flight power requirements, and (3) determining appropriate locations to accommodate the desired number of solar cells. A system model for flapping flight was also developed to predict payload capacity for carrying batteries to provide energy only for power spikes and to enable time-to-land safely in an area where batteries can recharge when the sun sets. The design framework was applied to a case study using flexible high-efficiency (>24%) solar cells on a flapping wing aerial vehicle platform, known as Robo Raven IIIv5, with the caveat that a powertrain with 81% efficiency is used in place of the current servos. A key finding was the fraction of solar flux incident on the wings during flapping was 0.63 at the lowest solar altitude. Using a 1.25 safety factor, the lowest value for the purposes of design will be 0.51. Wind tunnel measurements and aerodynamic modeling of the platform determined integrating solar cells in the wings resulted in a loss of thrust and greater drag, but the resulting payload capacity was unaffected because of a higher lift coefficient. A time-to-land of 2500 s was predicted, and the flight capability of the platform was validated in a netted test facility.Item Multipass Target Search in Natural Environments(MDPI, 2017-11-02) Kuhlman, Michael J.; Otte, Michael W.; Sofge, Donald; Gupta, Satyandra K.Consider a disaster scenario where search and rescue workers must search difficult to access buildings during an earthquake or flood. Often, finding survivors a few hours sooner results in a dramatic increase in saved lives, suggesting the use of drones for expedient rescue operations. Entropy can be used to quantify the generation and resolution of uncertainty. When searching for targets, maximizing mutual information of future sensor observations will minimize expected target location uncertainty by minimizing the entropy of the future estimate. Motion planning for multi-target autonomous search requires planning over an area with an imperfect sensor and may require multiple passes, which is hindered by the submodularity property of mutual information. Further, mission duration constraints must be handled accordingly, requiring consideration of the vehicle’s dynamics to generate feasible trajectories and must plan trajectories spanning the entire mission duration, something which most information gathering algorithms are incapable of doing. If unanticipated changes occur in an uncertain environment, new plans must be generated quickly. In addition, planning multipass trajectories requires evaluating path dependent rewards, requiring planning in the space of all previously selected actions, compounding the problem. We present an anytime algorithm for autonomous multipass target search in natural environments. The algorithm is capable of generating long duration dynamically feasible multipass coverage plans that maximize mutual information using a variety of techniques such as e-admissible heuristics to speed up the search. To the authors’ knowledge this is the first attempt at efficiently solving multipass target search problems of such long duration. The proposed algorithm is based on best first branch and bound and is benchmarked against state of the art algorithms adapted to the problem in natural Simplex environments, gathering the most information in the given search time.Item Overview of Assembly Modeling, Planning, and Instruction Generation Research at the Advanced Manufacturing Lab(Advanced Manufacturing Lab, 2012-12) Gupta, Satyandra K.Item Design, Manufacturing, and Testing of Robo Raven(2014-04) Gerdes, John; Holness, Alex; Perez-Rosado, Ariel; Roberts, Luke; Barnett, Eli; Greisinger, Adrian; Kempny, Johannes; Lingam, Deepak; Yeh, Chen-Haur; Bruck, Hugh; Gupta, Satyandra K.Most current bird-inspired flapping wing air vehicles (FWAVs) use a single actuator to flap both wings. This approach couples and synchronizes the motions of the wings while providing a variable flapping rate at a constant amplitude or angle. Independent wing control has the potential to provide a greater flight envelope. Driving the wings independently requires the use of at least two actuators with position and velocity control. Integration of two actuators in a flying platform significantly increases the weight and hence makes it challenging to achieve flight. We used our successful previous designs with synchronized wing flapping as a starting point for creating a new design. The added weight of an additional actuator required us to increase the wing size used in the previous designs to generate additional lift. For the design reported in this paper, we took inspiration from the Common Raven and developed requirements for wings of our platform based on this inspiration. Our design process began by selecting actuators that can drive the raven-sized wing independently to provide two degrees of freedom over the wings. We concurrently optimized wing design and flapping frequency to generate the highest possible lift and operate near the maximum power operating point for the selected motors. The design utilized 3D printed parts to minimize part count and weight while providing a strong fuselage. The platform reported in this paper, known as Robo Raven, was the first demonstration of a bird-inspired platform doing outdoor aerobatics using independently actuated and controlled wings. This platform successfully performed dives, flips, and buttonhook turns demonstrating the capability afforded by the new design.Item Overview of Geometry Based Indexing and Search Tool(2008-12) Gupta, Satyandra K.Item Characterization and control of plastic deformation in premolded components in in-mold assembled mesoscale revolute joints using bi-directional filling strategy(2008-12) Ananthanarayanan, Arvind; Gupta, Satyandra K.; Bruck, HughItem Towards a New Manufacturing Approach to Realizing Bio-Inspired Robots with Mesoscale Features(2010-12) Gupta, Satyandra K.