Abstract: A vehicular monitoring system (5) has a plurality of sensors (20, 30) that are used to sense the presence of objects (15) around a vehicle (10, 52) for detecting collision threats. At least one of the sensors is positioned such that a portion of the vehicle is at a predefined location relative to the sensor and is within the sensor's field of view. As an example, for an aircraft, a sensor may be positioned such that a portion of the aircraft's wing, aerospike, or other structure is within the sensor's field of view. The system is configured to automatically calibrate the sensor and, if desired, other sensors using the portion of the vehicle at the predefined location.

Abstract: A charging system for an autonomous data machine may be provided. The system may comprise: a charging station, wherein the charging station has a low profile allowing the autonomous data machine to drive over to charge a power supply of the autonomous data machine automatically; and one or more processors of the autonomous data machine configured to make charging decisions to effect charging operations of the autonomous data machine that include charging time, charging location, and operations to be performed during charging. In some instances, the charging decision are based on at least one of the following: location of charging station, availability of charging station, mission parameters, locations of other autonomous data machines, and/or charging requirements and/or availability of charging stations.

Abstract: Systems and methods are provided for improved security services. In one aspect, a method is provided for controlling an autonomous data machine situated near a monitored environment. The method comprises: obtaining security data from a plurality of data sources; analyzing the security data to generate an analysis result; determining, based on the analysis result, an action to be performed by the autonomous data machine; and transmitting a command to the autonomous data machine causing it to perform the action.

Abstract: A system for efficiently sensing collision threats has an image sensor configured to capture an image of a scene external to a vehicle. The system is configured to then identify an area of the image that is associated with homogeneous sensor values and is thus likely devoid of collision threats. In order to reduce the computational processing required for detecting collision threats, the system culls the identified area from the image, thereby conserving the processing resources of the system.

Abstract: The present disclosure generally pertains to systems and methods for detecting surface conditions using multiple images of different polarizations. A system in accordance with the present disclosure captures images having different polarizations and compares the images to evaluate surface conditions of an area, such as a runway, landing pad, roadway, or taxiway on which a vehicle is expected to land or otherwise travel. In some cases, a surface hazard, such as water, ice, or snow covering a surface of the area, may be detected and identified. Information indicative of the surface conditions may be used to make control decisions for operation of the vehicle.

Abstract: A monitoring system for an aircraft uses sensors configured to sense objects around the aircraft to generate a recommendation that is ultimately used to determine a possible route that the aircraft can follow to avoid colliding with a sensed object. A first algorithm generates guidance to avoid encounters with sensed airborne aircrafts. A second algorithm generates guidance to avoid encounters with sensed non-aircraft airborne obstacles and ground obstacles. The second algorithm sends inhibiting information to the first algorithm in a feedback loop based on the position of sensed non-aircraft objects. The first algorithm considers this inhibiting information when generating avoidance guidance regarding airborne aircrafts.

Abstract: A simulation testing architecture can be applied to an aircraft monitoring system for an aircraft that includes complex algorithms (such as machine learning algorithms) for sensing objects around the aircraft and controlling the aircraft to avoid such objects. A reference scenario is selected from a plurality of stored scenarios based on a desired set of aircraft safety standards. A stochastic process is applied to generate a large number of conditional variations within a simulated environment, varying weather, objects in the airspace, points of failure, and the like to provide a representative sample of possible aircraft missions and encounters within the selected reference scenario. Synthetic environmental inputs are fed into the aircraft monitoring system software, and the resultant actions of the software are logged. These logs can be used to generate metrics on an encounter-level basis, a scenario-level basis, or across a population of scenarios.

Abstract: A monitoring system for an aircraft can include an image sensor and a radar sensor. The system can provide noise compensation to a radar sample corresponding to a return radar signal received by the radar sensor based on information detected by the image sensor. The system can identify one or more object types in the image captured by the image sensor and then translate the identified object types to corresponding positions on a map. The system can correlate the radar sample to a position on the map and any object type located at that position can be identified. The system can then select a noise pattern that corresponds to the identified object type from the map and use the selected noise pattern to compensate the radar sample.

Abstract: Systems, methods, and devices for autonomous monitoring of parking areas are provided. In one aspect, a method for collecting information associated with a parking space includes providing a self-propelled autonomous data machine comprising one or more sensors. The autonomous data machine can be navigated to a location near a parking space for a vehicle. Parking information pertaining to the parking space can be obtained via the one or more sensors of the autonomous data machine. The obtained parking information can include at least occupancy data for the parking space. The parking information can be transmitted to a remote computing system configured to display the parking information to a user.

Abstract: A monitoring system for an aircraft has sensors configured to sense objects around the aircraft and provide data indicative of the sensed objects. The system contains a first type of computing module that processes data obtained from all the sensors and a second type of computing module dedicated to processing data from a particular sensor. The second module may characterize and locate a detected object within the processed image data. Both the first and second modules generate a likelihood of detection of an object within their processed image data. A scheduler module calculates a percentage of computing resources that should be assigned to processing data from a respective image sensor in view of this likelihood and assigns a dedicated compute module to an image sensor requiring a higher percentage of attention. Processing resources may therefore be focused on geospatial areas with a high likelihood of object detection.

Abstract: A monitoring system for an aircraft has sensors that are used to sense the presence of objects around the aircraft for collision avoidance, navigation, or other purposes. At least one of the sensors may be configured to sense objects around the aircraft and provide data indicative of the sensed objects. The monitoring system may use information from the sensor and information about the aircraft to determine an escape envelope including possible routes that the aircraft can follow to avoid colliding with the object. The monitoring system may select an escape path based on the escape envelope and control the aircraft to follow the escape path to avoid collision with one or more objects.

Abstract: A monitoring system for an aircraft has sensors configured to sense objects around the aircraft and provide data indicative of the sensed objects. A sense and avoid system is designed in a plurality of software layers, each layer functioning in an independent manner. An evasion software layer is made up of fixed, non-modifiable code that meets an applicable regulatory standard. The remainder of the software layers may be made up of modifiable or non-modifiable code configured so as not to adversely impact the functioning of an evasion software layer, even when modified. Each of the software layers of the sense and avoid system may use information from the sensors and information about the aircraft to generate a recommendation which is ultimately used to determine a possible route that the aircraft can follow to avoid colliding with the sensed object. The aircraft may then be controlled, in accordance with the recommendation, to avoid collision with the object.

Abstract: A monitoring system (5) for a vehicle (10) has sensors (20, 30) that are used to sense the presence of objects (15) around the vehicle for collision avoidance, navigation, or other purposes. At least one of the sensors (20), referred to as a “primary sensor,” may be configured to sense objects within its field of view (25) and provide data indicative of the sensed objects. The monitoring system may use such data to track the sensed objects. A verification sensor (30), such as a radar sensor, may be used to verify the data from the primary sensor from time-to-time without tracking the objects around the vehicle with data from the verification sensor.

Abstract: A vehicular monitoring system (5) has a plurality of sensors (20, 30) that are used to sense the presence of objects (15) around a vehicle (10, 52) for detecting collision threats. At least one of the sensors is positioned such that a portion of the vehicle is at a predefined location relative to the sensor and is within the sensor's field of view. As an example, for an aircraft, a sensor may be positioned such that a portion of the aircraft's wing, aerospike, or other structure is within the sensor's field of view. The system is configured to automatically calibrate the sensor and, if desired, other sensors using the portion of the vehicle at the predefined location.

Abstract: A charging system for an autonomous data machine may be provided. The system may comprise: a charging station, wherein the charging station has a low profile allowing the autonomous data machine to drive over to charge a power supply of the autonomous data machine automatically; and one or more processors of the autonomous data machine configured to make charging decisions to effect charging operations of the autonomous data machine that include charging time, charging location, and operations to be performed during charging. In some instances, the charging decision are based on at least one of the following: location of charging station, availability of charging station, mission parameters, locations of other autonomous data machines, and/or charging requirements and/or availability of charging stations.

Abstract: A monitoring system (5) for an aircraft (10) can modulate the range of a LIDAR sensor (30) on the aircraft (10) by increasing or decreasing the power level of the LIDAR sensor (30) in response to particular conditions at the aircraft (10). When the aircraft (10) is operating in a takeoff or landing mode, the range of the LIDAR sensor (30) is reduced to avoid possible eye damage to surrounding people or animals. As the aircraft (10) transitions to a cruise mode, the range of the LIDAR sensor (30) can be increased since the expectation is that there are no people or animals in the vicinity of the aircraft. If the system (5) detects the presence of an object (15) near the aircraft (10) during operation in cruise mode, the system (5) can determine if there is an eye safety concern associated with the object (15) and reduce the range of the LIDAR sensor (30) in the area around the object (15).

Abstract: An electric aircraft has a fault-tolerant electrical system designed to optimize competing concerns related to cost, performance, and safety. An electrical system in accordance with some embodiments of the present disclosure has a plurality of power sources (e.g., batteries) that are connected to other electrical components, such as motors for driving propellers or flight control surfaces, by a plurality of electrical buses. Each such bus is electrically isolated from the other buses to help the system better withstand electrical faults. Further, one or more of the electrical buses is connected to motors for driving multiple propellers. Selection of the propellers to be powered by energy received from the same bus is optimized so as to limit the effect of an electrical fault on the stability and controllability of the aircraft.

Abstract: A monitoring system for an aircraft has sensors that are used to sense the presence of objects around the aircraft for collision avoidance, navigation, or other purposes. At least one of the sensors may be configured to sense objects around the aircraft and provide data indicative of the sensed objects. The monitoring system may use information from the sensor and information about the aircraft to determine an escape envelope including possible routes that the aircraft can follow to avoid colliding with the object. The monitoring system may select an escape path based on the escape envelope and control the aircraft to follow the escape path to avoid collision with one or more objects.

Abstract: A monitoring system (5, 205) for an aircraft (10) has sensors (20, 30) that are used to sense the air movement around the aircraft. The monitoring system may use information from the sensors to estimate the effects of the air movement on the aircraft and to determine how to control components of the aircraft, such as flight control surfaces and a propulsion system, to compensate for such effects. The monitoring system may also assess aircraft performance based on the air movement information and provide control inputs for improving such performance. It is also possible for the monitoring system to determine more optimal flight paths for avoiding collision threats based on the air movement information.

Abstract: Autonomous data machines and systems may be provided, which may be deployed in an environment. The machines may roam within the environment and collect data with aid of one or more sensors. The data may be sent to a control center, which may optionally receive information from additional data sources, such as other on-site sensors, existing static data, or real-time social data. The control center may send instructions to the machines to perform one or more reaction based on the received information. The autonomous data machines may be capable of reacting autonomously to one or more detected condition. In some instances, the autonomous data machines may be employed for security or surveillance.