Abstract: An armor system for protecting vehicles and other equipment against projectiles and similar threats. A track is mounted on the equipment, and an upper sled and lower sled are moveably attached to the track. An armor panel is pivotally attached to one sled and is pivotally attached with arms to the other sled. The two sleds are independently actuated along the track, such that their relative positions determine both the translational and rotational position of the armor panel. The armor panel can be quickly rotated from an undeployed position against the vehicle through a desired arc outward from the vehicle, which increases the edge-on or nearly edge-on presentation of the armor panel to the projectile.

Abstract: An armor system for protecting vehicles and other equipment against projectiles and similar threats. A track is mounted on the equipment, and an upper sled and lower sled are moveably attached to the track. An armor panel is pivotally attached to one sled and is pivotally attached with arms to the other sled. The two sleds are independently actuated along the track, such that their relative positions determine both the translational and rotational position of the armor panel. The armor panel can be quickly rotated from an undeployed position against the vehicle through a desired arc outward from the vehicle, which increases the edge-on or nearly edge-on presentation of the armor panel to the projectile.

Abstract: A system of autonomous vehicles for forming a team of autonomous vehicles to perform a designated set of tasks. Each vehicle stores data representing its own capabilities that match the tasks, data representing needed capabilities for the team to perform the tasks, and data representing the capabilities of all current team members. Each of the vehicles is equipped with a communications system operable to send and receive join request messages and join response messages. All join request message contain the capabilities of the sending vehicle. All join response messages contain current team capabilities data. Upon receipt of a join request message, a vehicle compares needed capabilities data to the received capabilities data, and if there are matched capabilities, it updates the team capabilities data and transmits a join response message. Upon receipt of a join response message, if the message indicates the sending vehicle has joined the team, the receiving vehicle updates the team capabilities list.

Abstract: A method and system is provided for estimation of sensor data confidence based on statistical analysis of different classifier and feature-set (CF) configurations. A method may include: training a classifier of a CF configuration based on a training set of nominal sensor data values; executing the classifier on the training set to generate a first set of confidence values; collecting statistics on the confidence values; calculating a confidence decision threshold based on the collected statistics; executing the classifier on an evaluation set of nominal and degraded sensor data values, to generate a second set of confidence values; deciding whether the sensor data values of the evaluation set are nominal or degraded based on a comparison of the second set of confidence values to the confidence decision threshold; and calculating a score to evaluate the trained classifier based on a verification of the decisions.

Abstract: A system of autonomous vehicles for forming a team of autonomous vehicles to perform a designated set of tasks. Each vehicle stores data representing its own capabilities that match the tasks, data representing needed capabilities for the team to perform the tasks, and data representing the capabilities of all current team members. Each of the vehicles is equipped with a communications system operable to send and receive join request messages and join response messages. All join request message contain the capabilities of the sending vehicle. All join response messages contain current team capabilities data. Upon receipt of a join request message, a vehicle compares needed capabilities data to the received capabilities data, and if there are matched capabilities, it updates the team capabilities data and transmits a join response message. Upon receipt of a join response message, if the message indicates the sending vehicle has joined the team, the receiving vehicle updates the team capabilities list.

Abstract: A protective case for a smartphone is described, which includes a first frame part, and a second frame for retaining the smartphone therein. One frame part has a ball at an end thereof, the other includes a socket adapted to fixedly retain the ball therein. One of the frame parts is pivotable relative to the other via the ball and socket between open and closed states spanning up to 90 degrees, with one of the two frame parts further rotatable 360 degrees about its own longitudinal axis thereof via the ball and socket.

Abstract: A protective case for a smartphone is described herein. The case may include a first frame part, and a second frame for retaining the smartphone therein. One of the first and second frame part has a ball formed at one end thereof, and the other includes a socket adapted to fixedly retain the ball therein. The case further includes a threaded insert attachable to the case for receiving a tripod mount, and an elastomeric element. One of the frame parts is pivotable relative to the other via the ball and socket between open and closed states spanning up to 90 degrees, with one of the two frame parts further rotatable 360 degrees about its own longitudinal axis thereof via the ball and socket. The elastomeric element bears against the ball to provide friction so as to prevent undesired rotation of one frame part relative to the other in all degrees of freedom.

Abstract: A method and system is provided for estimation of sensor data confidence based on statistical analysis of different classifier and feature-set (CF) configurations. A method may include: training a classifier of a CF configuration based on a training set of nominal sensor data values; executing the classifier on the training set to generate a first set of confidence values; collecting statistics on the confidence values; calculating a confidence decision threshold based on the collected statistics; executing the classifier on an evaluation set of nominal and degraded sensor data values, to generate a second set of confidence values; deciding whether the sensor data values of the evaluation set are nominal or degraded based on a comparison of the second set of confidence values to the confidence decision threshold; and calculating a score to evaluate the trained classifier based on a verification of the decisions.