Commercial drones (unmanned aerial vehicles–UAVs, sold directly to a business for use in its operations) is a fast-growing market segment, with worldwide sales expected to reach 2.4 million units in 2023–increasing at a 66.8% compound annual growth rate (CAGR). The main commercial drone end markets include agriculture, construction and mining, insurance, media and telecommunications, and law enforcement.
With the market for more expensive, sophisticated drones growing steadily, so does the need for a reliable collision avoidance technology to protect the precious aircraft as well as the people and objects crossing their flight path. Accidents involving drones tend to be highly publicized, and legislative bodies are beginning to take concrete actions to regulate drone usage in order to prevent the occurrence of accidents and the potential for fatalities. On the supplier side, drone manufacturers are actively seeking to integrate anti-collision systems into their products as their customers aim to stay clear of newspaper headlines due to navigation incidents.
As a result, increasing investment is being made every year to develop and deploy reliable systems that make drones more aware of their environment. Yet, when it comes to drones, not all perception technology is created equal.
True Collision Avoidance: Easier Said Than Done
Today, most drone models have some degree of assisted navigation features, sometimes marketed as “collision avoidance”. However, a bit of research reveals that some of these systems present significant limitations (unidirectional, very short ranges, very slow speeds, etc.) or only provide limited feedback or alarm to the pilot (e.g., beeping on the remote control if an obstacle is detected). There are still very few fully autonomous systems that can provide reliable sense-and-avoid capabilities for commercial UAVs. Such systems should be capable of detecting all potential obstacles, assessing the risk of collision, and taking evasive actions by themselves, overriding the pilot’s input if needed.
Interestingly, the challenges related to commercial drones’ awareness of their immediate environment are quite similar between the entry-level quadcopter and the fully loaded customized UAV. The sensors used necessitate a similar combination of requirements: compact form-factor, robustness, sufficient range, wide field of view, performance in any lighting conditions, processing efficiency, and, of course, a reasonable price point. Some use cases require the recognition of hard-to-detect obstacles such as a high-voltage line or a chain link fence. All the aforementioned elements are essential to the successful deployment of reliable autonomous collision avoidance systems in commercial drones.
Yet, many of today’s sense-and-avoid solutions fall short in performance when faced with real-life conditions (as well as with some admittedly hard-core pilots); GPS and barometers aren’t full-proof– even outdoors –and can’t be relied upon when navigating indoors; ultrasonic systems are cheap and lightweight but lack the required range; optical flow sensors require good lighting and textured surfaces; and camera vision is vulnerable to changing light conditions and remains processing-intensive. In this context, LiDAR truly sets itself apart as a top-performing sensing technology, just as it has established itself as an essential sensing solution in other types of mobility applications. LiDAR has gained significant traction among drone and unmanned vehicle manufacturers thanks to its many advantages over traditional sensing technologies such as radar and sonar.
Take-Off, Hovering, and Landing
In order to manage take-offs, hover in place, and avoid hitting the ground or obstacles upon landing, many UAVs rely on information from GPS and pressure sensors. This may become problematic when navigating in urban canyons and inside structures as well as during indoor operations. Some drone vendors provide ultrasound (sonar) sensors which can typically reach an above ground level (AGL) height of up to 5 or 6 m. The sonar is sometimes coupled with an optical flow camera, which can survey the ground and ensure lateral stability.
Increasingly, drone manufacturers opt for an optical altimeter based on LiDAR technology for its precise distance measurement to the ground as well as the superior distance range provided compared with ultrasonic sensors. This range will typically vary with the optical power of the light source: eye-safe power sources, such as LED and Class 1 lasers, are favored over more powerful lasers, which may bring safety restrictions. Highly optimized optical range finders, such as the LeddarOne are being implemented in new generations of commercial drones.
Indoor Navigation and Collision Avoidance
Indoor navigation, which renders GPS and pressure sensors ineffective, is one of the main challenges faced by today’s UAVs. Commercial drones may be required to fly into a damaged building, or to navigate inside sewer lines, or even into hydro dam turbines! Sensors capable of providing precise, reliable information about the drone’s immediate surroundings and any obstacles along the way, including accurate distance information, are paramount to safe, successful flight missions.
One solution is to use a multi-segment LiDAR sensing solution such as the Leddar Vu8 flash LiDAR, which provides reliable obstacle detection in both indoor and outdoor settings, thanks to its use of a wide infrared light beam to precisely measure distances from the returned signal. Moreover, the Vu8’s efficient data processing provides precise positioning data while minimizing power consumption and external processing requirements.
Scanning Vs. Solid-State LiDAR
Scanning LiDARs, widely used in high-resolution 3D terrain mapping applications, can generate a detailed rendering of their surroundings by spinning or swiveling single-point collimated lasers. Scanning LiDARs can be expensive and are built with mechanical components that make them more prone to failure.
Solid-state LiDARs, including flash LiDARs, on the other hand, use a fixed, diffuse light source that serves as the detection medium and illuminates the sensor’s whole field of view at once without any moving parts. This makes them smaller, lighter, affordable, and very durable. As mentioned previously, solid-state LiDARs like the Leddar Vu8 also have the advantage of generating a lower, more optimized data output, which translates to less processing requirements.
The Reference in Solid-State LiDAR
Bridging the cost/performance gap in LiDAR technology, LeddarTech has developed patented, highly optimized algorithms that brings solid-state LiDAR sensing to the next level. Rather than working directly on the analog signal like traditional LiDARs do, LeddarTech’s digital signal processing technology iteratively expands the sampling rate and resolution using multiple successive light pulses. It then analyzes the resulting discrete-time signal to recover the distance for every object present in its field of view. The complete digitized waveform holds lots of information that is processed to generate more reliable measurements in a wider range of conditions than traditional time-of-flight LiDAR methods, resulting in a much higher effective dynamic range for precise obstacle and ground detection.
Because of these unique characteristics, LeddarTech’s innovative solid-state LiDARs have been adopted by leading drone manufacturers worldwide to deploy highly reliable altimetry and collision avoidance applications.
Find out more on LiDAR solutions for drones and UAVs at www.leddartech.com/drone
Founded in 2007, LeddarTech is a comprehensive end-to-end environmental sensing company that enables customers to solve critical sensing, fusion and perception challenges across the entire value chain. LeddarTech provides cost-effective perception solutions scalable from Level 2+ ADAS to Level 5 full autonomy with LeddarVision™, a raw-data sensor fusion and perception platform that generates a comprehensive 3D environmental model from a variety of sensor types and configurations. LeddarTech also supports LiDAR manufacturers and Tier 1-2 automotive suppliers with key technology building blocks such as LeddarSteer™ digital beam steering and the LiDAR XLRator™, a development solution for automotive-grade solid-state LiDARs based on the LeddarEngine™ and core components from global semiconductor partners. The company is responsible for several innovations in cutting-edge automotive and mobility remote-sensing applications, with over 100 patented technologies (granted or pending) enhancing ADAS and autonomous driving capabilities.