Sense and Avoid Sensor Selection

            Sense and avoid is a critical piece of operating all types of aircraft, both manned and unmanned alike.  Unmanned aircraft however, do are not afforded the same flexibility and reliability of the human eye and brain to see obstacles and other traffic.  For this reason, unmanned aircraft must rely on complex sensors and computer algorithms to detect and avoid objects.  Small unmanned aerial systems pose a particular challenge to this requirement due to their small nature and low power requirements. Due to these limiting factors, when designing detect and avoid sensor packages for small unmanned aerial vehicles is that they must be size, weight, power and cost (SWaP-C) optimized, while still being able to provide top-notch detection and avoidance capabilities.  There are many approaches that can be taken and sensors available to create a detect and avoid system for small unmanned system such as light detection and ranging (LIDAR), ultrasonic sensors, electro-optical sensors (cameras), and even small radar systems.  Proper selection of these systems is important, as each has its pros, cons and limitations; making no one type a perfect all-around solution (Corrigan, 2018).

            One system that is currently being developed is the Iris Automation Collision Avoidance System (Figure 1).  The system, designed and built by Iris Automation utilizes computer vision (Figure 2) and advanced algorithms to detect obstacles such as aircraft, terrain and even wildlife.  Utilizing a monocular vision camera system and advanced algorithms that generate a highly detailed and robust computer vision image, the collision avoidance system can reliably detect, track and avoid both static and moving obstacles (Technology, n.d.).  Monocular vision sensors enable single images to be processed to create three-dimensional spatial reconstructions.  With the reconstructions distances can be determined by comparing real-time images captured by the camera to pictorial depth cues that are programmed into complex algorithms.  Monocular systems are commonly seen on small unmanned vehicle due to their low cost, weight and power requirements (Corrigan, 2018).

 

Figure 1: Iris Collision Avoidance System (Technology, n.d.)

 

Figure 2: Computer Vision Example (Technology, n.d.)

The system is designed to be highly modular and configurable so that users can incorporate varying numbers of cameras for up to 360-degree situational awareness.  Additionally, the system will be available as a software only package so that users can integrate 3^rd party sensors into the system via a seamless plug-and-play interface.  This allows the vision system to be fitted to nearly any type of small unmanned system including single and multi-rotor helicopters and fixed wing aircraft.  The collision avoidance system is designed to be rugged and is built to MIL Spec standards and has been tested in varying and extreme weather conditions and environments.  While the specific details of the size, weigh, power and cost are not yet available because the system is still in the design and testing phase, Iris Automation has promised that this system will be ultra-low SWAP-C optimized and the perfect addition for any small unmanned aerial vehicle (Technology, n.d.).

            To further prove the capabilities of the Iris Collision Avoidance System, several tests have been completed utilizing a life flight with a manned aircraft for the system to detect and avoid.  During one such test, the obstacle aircraft (manned Cessna 162) made three passes varying distances.  The first two passes were conducted at 150 meters and 200 meters respectively.  On each pass the detection system was able to not only detect and track the aircraft, but also determine its distance from the unmanned vehicle and provide a baseline classification of the size of the obstacle aircraft (Figure 3).  On the third pass, the obstacle aircraft can within approximately 500 meters of the unmanned vehicle.  During this pass the system was able to reliably detect and track the aircraft but was not able to classify the aircraft size.  This test proves the reliability of the system to detect and track even distant objects to ensure full awareness is realized (Technology, n.d.).

 

Figure 3: Example of what vision system sees.  Image captured of first pass at about 150 meters (Technology, n.d.)

            Overall the Iris Automation Collision Avoidance System is a perfect fit for almost all types of small unmanned aerial vehicles.  Its small size, weight and power requirements combined with its expected low cost will make it not only easy to integrate into all types of vehicles, but it will make it easily attainable to even the most entry level consumer in the drone industry and market.

References

Corrigan, F. (2018, June 17). Top Collision Avoidance Drones And Obstacle Detection Explained. Retrieved August 17, 2018, from https://www.dronezon.com/learn-about-drones-quadcopters/top-drones-with-obstacle-detection-collision-avoidance-sensors-explained/

Technology. (n.d.). Retrieved August 17, 2018, from https://www.irisonboard.com/technology/

Ground Control Station Analysis

            There are many options for control stations available to unmanned system operators.  Many of them come with a plethora of features and tools for data processing and analysis, and some are even capable of multiple vehicle control.  One such system that is capable of multi-domain vehicle control is the Portable Ground Control Station by Octopus ISR Systems (Figure 1).  This system is a highly modular, dual display control station that can serve as the main command and control system for a variety of unmanned systems in the ground, air and sea domains (Ground Control Station, n.d.).

Figure 1: Portable Ground Control Station (UAV Factory, n.d.)

            The Portable Ground Control Station is a highly flexible and robust system that can adapt to many types of unmanned vehicles.  Designed to be compact and portable, the ground control station is designed into a carrying case measuring 1000mm x 420mm x 170mm and weighing at a total of only 18.9 kilograms.  Additionally, the control station is mounted to the inside of the case enabling its operators to set it up and tear it down in minimal amounts of time.  The system is powered by two lithium batteries that can be changed out without restarting the control station, making it ideal for long duration missions where a direct power connection is not available.  The control station really makes it money through its modular electronics compartment (MEC) (Figure 2).  This compartment is designed to fit a wide variety of addon hardware and features a host of connectors for seamless integration, basically making adding sensors and additional features as simple as plug-and-play (Ground Control Station, n.d.).  The MEC can supply power anywhere from 10-32 volts of direct current, allowing it to fit additional equipment such as datalink systems, video receivers, data storage and recording devices.  The control station is also equipped with two pass-through antennae for communications (UAV Factory, n.d.).   This flexibility allows the control station to shine amongst others by being adaptable to many different types of unmanned vehicles.

Figure 2: Modular Electronics Compartment (MEC) (Ground Control Station, n.d.)

            The interface for the Portable Ground Control Station is developed around the Panasonic CF-31 Toughbook (Figure 3), which serves as the processing hub for the data that is collected and the command and control processes.  The Toughbook is connected via a docking station to the control station and is augmented by a 17-inch, high-brightness touchscreen display that is built into the carrying case.  The components added to the MEC can be connected to these displays via several types of connectors including USB, ethernet, serial ports, video inputs, VGA, and audio connectors.  This allows the added modules to project data onto either the 17-inch touch screen or the Toughbook for processing and analysis (UAV Factory, n.d.).  The integration of the Toughbook allows each user to customize the software that is used so that it can perfectly match their mission and so that there are minimal restrictions on the types of software that can be utilized with the Portable Control Station.

Figure 3: Panasonic CF-31 Toughbook (Ground Control Station, n.d.)

            There are very few limitations to this design due to its highly modular and flexible nature.  One of the limitations to this system is its size.  While it is overall fairly small and light, it is not small enough to be carried in a backpack for into the field through rugged terrain.  This means that the Portable Ground Control Station would need to be setup at a basecamp type area to be able to conduct missions.  This could potentially limit some users on where they can collect data and fly their missions.  One option would be to reduce the size of the system by decreasing the size of the MEC or by removing the 17-inch touchscreen display, however this would reduce the flexibility in the system for its users.  Size a flexibility always come with tradeoffs, but these options could provide some more portability for the system, which could be ideal for some users.

            Another limiting factor is that this control station is designed to be only have one operator.  This could pose a problem if the unmanned vehicle being used has complex sensors and payloads that require two operators to be used effectively.  The small size of the system does not allow for side-by-side work of two operators, nor does it have two sets of controls for control of the vehicle and of any sensors.  A second set of controls could potentially be added via the MEC, however it would create a cramped working environment for the two operators.  One possibility to overcome this issue would be to connect two control stations together.  This would allow one station to be used for an operator to control the vehicle, and one for an operator to control any payloads required for their mission. 

References

GROUND CONTROL STATION. (n.d.). Retrieved August 10, 2018, from http://octopus.uavfactory.com/uav-payloads-equipment/portable-ground-control-station

UAV Factory. (n.d.). [Brochure]. Author. Retrieved August 10, 2018, from http://www.uavfactory.com/product/16