Thermal imaging odometry and navigation systems and related techniques are provided to improve the operational flexibility of autonomous/unmanned vehicles. A thermal imaging odometry system includes a thermal imaging module configured to be coupled to an unmanned vehicle, a ranging sensor system fixed to the thermal imaging module, and a logic device. The thermal imaging module provides thermal imagery of a scene in view of the unmanned vehicle and centered about an optical axis of the thermal imaging module, where the optical axis is fixed relative to an orientation of the unmanned vehicle. The ranging sensor system provides ranging sensor data indicating a standoff distance between the thermal imaging module and a surface intersecting the optical axis of the thermal imaging module. The logic device receives thermal images of the scene and corresponding ranging sensor data and determines an estimated relative velocity of the unmanned vehicle.

Thermal imaging odometry and navigation systems and related techniques are provided to improve the operational flexibility of autonomous/unmanned vehicles. A thermal imaging odometry system includes a thermal imaging module configured to be coupled to an unmanned vehicle, a ranging sensor system fixed to the thermal imaging module, and a logic device. The thermal imaging module provides thermal imagery of a scene in view of the unmanned vehicle and centered about an optical axis of the thermal imaging module, where the optical axis is fixed relative to an orientation of the unmanned vehicle. The ranging sensor system provides ranging sensor data indicating a standoff distance between the thermal imaging module and a surface intersecting the optical axis of the thermal imaging module. The logic device receives thermal images of the scene and corresponding ranging sensor data and determines an estimated relative velocity of the unmanned vehicle.

An aircraft collision avoidance system includes a plurality of three-dimensional (3D) light detection and ranging (LIDAR) sensors, a plurality of sensor processors, a plurality of transmitters, and a display device. Each 3D LIDAR sensor is enclosed in an aircraft exterior lighting fixture that is configured for mounting on an aircraft, and is configured to sense objects within its field-of-view and supply sensor data. Each sensor processor receives sensor data and processes the received sensor data to determine locations and physical dimensions of the sensed objects. Each transmitter receives the object data, and is configured to transmit the received object data. The display device receives and fuses the object data transmitted from each transmitter, fuses the object data and selectively generates one or more potential obstacle alerts based on the fused object data.

An aircraft collision avoidance system includes a plurality of three-dimensional (3D) light detection and ranging (LIDAR) sensors, a plurality of sensor processors, a plurality of transmitters, and a display device. Each 3D LIDAR sensor is enclosed in an aircraft exterior lighting fixture that is configured for mounting on an aircraft, and is configured to sense objects within its field-of-view and supply sensor data. Each sensor processor receives sensor data and processes the received sensor data to determine locations and physical dimensions of the sensed objects. Each transmitter receives the object data, and is configured to transmit the received object data. The display device receives and fuses the object data transmitted from each transmitter, fuses the object data and selectively generates one or more potential obstacle alerts based on the fused object data.

The present disclosure relates to a method for determining an action for collision avoidance in a craft. The method (100) comprises obtaining (110) object data comprising three-dimensional object data points (420); obtaining (120) state data of the craft (260); determining (140) at least one set of manoeuvre paths (410a,b,c) for the craft (260) based on the obtained craft state data; determining (150) a set of distance thresholds (421) for the three-dimensional object data points (420) based on the object data; comparing (160) each set of manoeuvre paths (410a,b,c) with the object data and the set of distance thresholds (421), wherein the set of manoeuvre paths (410a,b,c) is identified as a colliding set of manoeuvre paths (410a,b,c) when each path of the set of manoeuvre paths (410a,b,c) is at least partially within the corresponding distance threshold (421) of at least one three-dimensional object data point (420); and determining (170) an action upon identification of at least one colliding set of manoeuvre paths (410a,b,c).

A target acquisition system includes a transmitter configured to emit a plurality of pulses at a plurality of transmit times toward a target, a receiver configured to detect a plurality of photon arrival events at a plurality of receive times, and a processor configured to determine a range of the target and a range-rate of the target by identifying a subset of the receive times and a subset of the transmit times, generating scaled transmit times based on the subset of the transmit times and a plurality of trial target velocities relative to the receiver, cross-correlating the scaled transmit times and the subset of the received times to generate a plurality of cross-correlation power values, and calculating the range and the range-rate of the target based on the plurality of cross-correlation power values.

The method can include: determining sensor information with an aircraft sensor suite; based on the sensor information, determining a flight command using a set of models; validating the flight command S130; and facilitating execution of a validated flight command. The method can optionally include generating a trained model. However, the method S100 can additionally or alternatively include any other suitable elements. The method can function to facilitate aircraft control based on autonomously generated flight commands. The method can additionally or alternatively function to achieve human-in-the-loop autonomous aircraft control, and/or can function to generate a trained neural network based on validation of autonomously generated aircraft flight commands.

The method can include: determining sensor information with an aircraft sensor suite; based on the sensor information, determining a flight command using a set of models; validating the flight command S130; and facilitating execution of a validated flight command. The method can optionally include generating a trained model. However, the method S100 can additionally or alternatively include any other suitable elements. The method can function to facilitate aircraft control based on autonomously generated flight commands. The method can additionally or alternatively function to achieve human-in-the-loop autonomous aircraft control, and/or can function to generate a trained neural network based on validation of autonomously generated aircraft flight commands.

A system for generating a three-dimensional (3D) map of part of a field-of-view (FOV) of at least one detector of an active 3D scanner, the system comprising: the active 3D scanner, comprising: a scanning mechanism configured to scan the FOV; at least one energy emitting source configured to emit energy pulses, in synchronization with the scanning mechanism, to cover the FOV; and the at least one detector: and processing circuitry configured to: obtain mapping designation information independent of past readings obtained by the at least one detector, if any; selectively activate the energy emitting source to emit only a subset of the energy pulses, in accordance with the mapping designation information, to cover the part of the FOV; obtain current readings, from the at least one detector, based on reflections of the subset of the energy pulses; and generate the 3D map based on the current readings.

A light detection and ranging (LIDAR) system has a modulator to modulate a light signal from an optical source with a low-power mode at a section of a sweep signal to generate a pulsed light signal transmitted towards a target. The LIDAR system has a photodetector to receive a return beam from the target with an amplitude modulated (AM) signal portion and a frequency modulated (FM) signal portion. The LIDAR system processes the return beam with in-phase/quadrature (I/Q) detection to extract the AM signal portion and the FM signal portion. The system determines a range value and a velocity value for the target based on the extracted AM signal portion and the extracted FM signal portion.