Sikorsky Aircraft Corporation

Stevens Institute of Technology

Schlumberger Technology Corporation

Massachusetts Institute of Technology

Brendan Englot

Harshad S Sane

Eui-Hyeok Yang, Jr

Chang-Hwan Choi

Jian Xu

Wei Xu

Igor Cherepinsky

Jason C Derenick

Thomas A Frewen

Christopher Stathis

George Nicholas Loussides

Xuchu Ding

Ronald Besser

Timothy Paul Osedach

Jinkun Wang

Tixiao Shan

Smart membranes are integrated into a small, unmanned surface vessel to enable the efficient, automated cleanup of oil spills. Such a vessel has the potential to provide a low-cost, modular solution for day-to-day oil-spill cleanup operations, especially in confined aquatic areas (e.g., under piers or in the small spaces between marine vessels and piers). The membranes are provided on the surface of a conveyor belt that circulates the membranes through the surrounding body of water for oil collection, as well as through an internal reduction chamber of the vessel for oil release. The smart membranes are adapted to attract and repel oil in response to low-voltage commands applied across the conveyor belt, using a process that is repeatable for a number of cycles, offering high efficiency and long durability. Segments of the conveyor belt can be electrically isolated from one another to allow disparate electrical potentials to be imposed thereon.

In situ oil cleanup and recovery using smart polymer integrated surface vessels

Smart membranes () are integrated into a small, unmanned surface vessel () to enable the efficient, automated cleanup of oil spills. Such a vessel () has the potential to provide a low-cost, modular solution for day-to-day oil-spill cleanup operations, especially in confined aquatic areas, such as under piers and in the small spaces between marine vessels and piers. The smart membranes () are provided on the surface of a conveyor belt () that circulates the membranes () through the surrounding body of water () for oil collection, as well as through an internal reduction chamber () of the vessel () for oil release. The smart membranes () are adapted to attract and repel oil () in response to low-voltage commands applied across the conveyor belt (), using a process that is repeatable for a number of cycles, offering high efficiency and long durability (FIG.).

Embodiments of the present disclosure are directed towards a system and method for performing an inspection of an underwater environment. Embodiments may include providing an autonomous underwater vehicle ('AUV') and performing an inspection of an underwater environment using the AUV. Embodiments may further include acquiring real-time sensor data during the inspection of the underwater environment and applying an active simultaneous localization and mapping (“SLAM”) algorithm during the inspection, wherein applying includes estimating one or more virtual landmarks based upon, at least in part, at least one past measurement and a current estimate of AUV activity.

System and method for autonomous exploration for mapping underwater environments

According to an aspect of the invention, a method of optimal safe landing area determination for an aircraft includes accessing a probabilistic safe landing area map that includes a plurality of probabilistic indicators of safe landing areas for the aircraft. A processing subsystem that includes one or more processing resources generates a list of candidate safe landing areas based on the probabilistic safe landing area map and one or more constraints. At least two of the candidate safe landing areas are provided to a path planner. The list of candidate safe landing areas is ranked based on results from the path planner indicating an estimated cost to reach each of the candidate safe landing areas. Based on the ranking, an indicator of an optimal safe landing area is output as a desired landing location for the aircraft.

Optimal safe landing area determination

A method for path planning for a plurality of vehicles in a mission space includes determining, with a processor, information indicative of a first local graph of a first vehicle; receiving, with the processor over a communication link, information indicative of a second local graph from a second vehicle; assembling, with the processor, information indicative of a global graph in response to the receiving of the second local graph; wherein the global graph includes information assembled from the first local graph and the second local graph; and wherein the global graph indicates connectivity of objectives for each vehicle of the plurality of vehicles in the mission space.

Coordinated planning with graph sharing over networks

An aspect includes space partitioning for vehicle motion planning. A plurality of obstacle data is analyzed to determine a plurality of obstacle locations in a configuration space of a vehicle. A partitioning of the configuration space is performed to compute a skeletal partition representing a plurality of obstacle boundaries based on the obstacle locations. The skeletal partition is used to preferentially place a plurality of samples by a sampling-based motion planner. At least one obstacle-free path is output by the sampling-based motion planner based on the samples.

Space partitioning for motion planning

A method of route planning for a vehicle proceeding from a current location to a destination in a planning space is provided. The method includes generating a destination-rooted tree from global information that provides cost-to-go routing to the destination from multiple locations in the planning space, generating a vehicle-rooted tree using local information from the current location out to a sensing horizon and determining a local destination at the sensing horizon. The local destination corresponds to minimal cost-to-go routing obtained from the destination-rooted tree.

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New York, NY, United States of America

Brendan Englot