LiDAR, an acronym for “light detecting and ranging,” is a light-based echolocation technology. Unlike radar that uses radio waves in much lower frequency to penetrate fog, smog, haze, rain, snow, and drizzle, LiDAR uses light waves to create a more accurate representation of objects in its path.
LiDAR works by bouncing pulses of lasers off objects and measuring the time the light takes to reflect the sensor. Most self-driving vehicles use roof-mounted LiDARs that rotate, send a pulse of light 360 degrees around the vehicle for identifying nearby objects and create a 3D view of the surroundings. LiDAR plays an indispensable role in autonomous cars as their “seeing eyes.” Without LiDAR, autonomous vehicles would be driving blind.
LiDAR is also an essential sensor used in advanced vehicle driver assist systems (ADAS), such as automated cruise control, collision avoidance systems, and emergency braking systems, offered on many new vehicles today.
However, there are many inherent challenges in LiDAR to overcome in terms of cost, size, and reliability. The current commercial LiDAR units are bulky, sensitive to disruption, and expensive, costing up to $75,000. They use large, rotating mirrors to steer the laser beam and to create a 3-D image. To make LiDAR smaller, more robust, and cheaper, researchers and companies worldwide are working on several prototypes that can go into robots and autonomous vehicles, enabling them to navigate complex environments and dynamically avoid obstacles.
For instance, Volvo is to incorporate its LiDAR-based obstacle detection units from Luminar into some of its cars by 2022. Self-driving technology startup Aurora is developing an in-house LiDAR system “FirstLight” for its driverless vehicles, that can see and track objects quickly and far better than other LiDAR sensors.
Progress in this technology will eventually provide machine vision applications for most robots, dramatically increasing their flexibility, situational awareness, and ability to work in close collaboration with humans. In this post, we will look at some of the crucial breakthroughs and progress achieved by researchers in the development of LiDAR.
1. Leddar Tech
Leddar Tech is developing solid-state LiDAR resistant to mechanical disruption, which can cause significant errors in traditional LiDAR systems. Importantly, their technology provides the same or better levels of sensitivity as other systems that use expensive lasers and mirrors for tasks such as accurate time-of-flight measurements and clear signal-to-noise ratios using inexpensive LEDs. Their hardware and software algorithms permit a high sampling rate and may provide highly efficient machine vision for industrial robots subjected to challenging environments or occasional jostling.
The cameras made by Leddar Tech are relatively small and are more sensitive than traditional LiDAR systems; however, Leddar’s cameras currently have a narrow view. Depending on the application, they would potentially require the use of multiple devices to achieve a sufficiently broad field. These cameras are currently being investigated for use in self-driving cars. Still, they could easily be adapted to a wide array of applications, mainly because of their small size, robustness, and relatively low price point.
2. Photonics Microsystems Group
The Photonics Microsystems Group at MIT is working to dramatically miniaturize LiDAR systems by integrating them onto microchips. These chips can be produced in commercial CMOS foundries on standard 300-millimeter wafers, potentially making their unit production cost about $10. This chip has some limitations, since the current steering range of the beam is about 51 degrees, and it cannot create a 360-degree image by itself. Their chips can only detect objects at 2 meters, but they are working on chips with a range of 100 meters.
Because of their small size and relatively inexpensive manufacturing costs, these chips have the potential to include multiple LiDAR sensors on a single device and expand machine vision applications to even basic consumer-facing robots. Inexpensive 360-degree vision achieved with arrays of these chips for robots would offer safe and effective collision avoidance, responsiveness to human gestures, and more adaptable designs.
3. Takashima Lab
The Takashima Lab at the University of Arizona is another group working on the miniaturization of LiDAR systems. Laser beam steering is a critical component of LiDAR image reconstruction and analysis, which usually contributes significantly to the bulk, expense, and fragility of LiDAR devices. At the SPIE Opto 2018 meeting, J. Rodriguez et al. demonstrated a small and inexpensive 3D-printed LiDAR detection system on a chip.
While some groups are exploring micro-electromechanical systems for LiDAR beam steering, this group has developed a digital micromirror device that is relatively small and provides an improved field of view relative to current LiDAR systems (48 degrees instead of 36 degrees) and a large beam size that is on par with existing LiDAR systems. While the present limitation of this approach is a reduced number of scanning points, the Takashima Lab and others are developing a multi-laser diode detector that may overcome this issue. Overall, this strategy shows some promise, with several devices showing moderate range despite the low cost and the ease of manufacture.
Once developed and available, these chip-based LiDAR systems may be ideal for a suite of short-distance applications such as the detection of nearby obstacles and visually identifying objects to grab or manipulate. For example, robots with these sensors could be used to assemble or disassemble complex machines and classify objects by sight in shipping fulfillment centers, or these chips could be used in miniaturized pipeline inspection robots.
4. Gopinath Lab
Liquid lens-based autofocusing of light facilitates robust real-time control of the light used in LiDAR sensing. Gopinath Lab at the Colorado University explores the concept, using a weak electromagnetic current to manipulate the shape of several lenses. This technology is currently commercially available for other applications. It is being sold by companies such as Cognex, which provides off-the-shelf tunable liquid lenses for directing and concentrating lasers.
These lens systems are mechanically robust as they do not require the movement of physical parts to direct the laser path. The system is also relatively inexpensive for new application development, as it is already in production. These factors will potentially make this technology ideal for LiDAR applications, particularly in cases where the robot must be able to rapidly change the focus of the objective.
5. University of Colorado Boulder
Researchers at the University of Colorado Boulder made a breakthrough in LiDAR technology by creating a new silicon chip with no moving parts or electronics that improve the resolution and scanning speed needed for a LiDAR system. For three years, the team has been working on a way of steering laser beams, called wavelength steering, in which each wavelength or color is pointed to a unique angle to create 3D images.
According to a paper titled “Serpentine optical phased arrays for scalable integrated photonic LiDAR beam steering, published in the journal Optica, they’ve not only developed a way to do a version of this along two dimensions simultaneously, instead of only one, but they’ve also done it with color, using a “rainbow” pattern to take 3-D images. Since the beams are easily controlled by simply changing colors, multiple phased arrays can be controlled simultaneously to create a bigger aperture and a higher resolution image. The simpler and smaller these silicon chips are while retaining high resolution and accuracy, the more technologies they can be applied to, including self-driving cars and smartphones.
