Monday, June 19, 2017

Hokanen in Mems Journal

There's much more at the source. 

Re-posted by Microvision today.






MEMS Journal: Why did you choose to form a partnership to co-develop your LBS technology with ST Microelectronics and what does the partnership involve?
Jari Honkanen: We formed a close working relationship with STMicroelectronics over the past several years and recognized common interests and complementary skills in the LBS technology arena.  The co-marketing agreement is a framework for us to work collaboratively on sales and marketing of our respective LBS solutions.  We are also exploring the possibility of future technology development including a joint-LBS roadmap.  Bringing our complementary skills together to grow the market for LBS and applications that both companies are focusing on makes good sense, and both companies benefit from the relationship.  We benefit from ST’s expertise in semiconductor technology and its global customer reach, while ST benefits from our proprietary system, LBS engine and applications knowledge, and intellectual property.



MEMS Journal: Let’s switch topics a bit.  There are many companies pursuing LIDAR.  What is your take on this ADAS sensor technology and what are the main trends?

Jari Honkanen: LIDAR is one of the key enabling sensor technologies for ADAS, and eventually for self-driving vehicles, that enable cars to “see.”  In the current prototype systems, a single LIDAR sensor is typically used for long range environmental mapping and modeling.  However, there is an industry debate going on whether camera sensors, radar, or LIDAR is the best technology for this purpose. 

Camera sensors can be used to capture video of the environment and then the ADAS system can utilize computer vision algorithms to make sense of and analyze the environment.  What’s great about camera sensors is that one can distinguish and classify complex objects such as traffic signs or lane markings, as well as pedestrians or animals.  The challenge is that the camera can only see what it can see -- in other words, camera sensors have challenges in low light and bright sun light.  Also the vision algorithms require significant computing power.

When equipped with a radar sensor, the car transmits radio waves and interprets the back reflection.  Radar works great for the detection of large objects and can easily calculate speed and distance.  It also works on all weather and lighting conditions.  However, the challenge with radar is that it cannot distinguish color or differentiate between objects of the same size. 

Finally, LIDAR transmits light pulses and interprets the back reflection from objects.  The major benefit of LIDAR is that it can classify and detect specific objects and calculate distance.  It can also detect things like lane edges and it works during both dark and light conditions.  However, the challenge of LIDAR is that in inclement weather conditions the light can reflect from rain, snow or fog, reducing the sensor’s effectiveness.

These different sensor technologies have their strengths and weaknesses.  Hence, for the foreseeable future, cars will have to rely on a combination of these sensors.  This may also be desired for redundancy and safety.  The car industry can look to the aviation industry when it comes to redundancy and backup systems for safety.

But besides a single long range LIDAR for environment mapping and modeling, we believe that ADAS will have many applications for cost effective mid-range LIDAR systems.  We envision future cars to contain multiple mid-range LIDAR sensors performing a variety of ADAS applications, such as blind spot detection, parking assist, lane assist and departure warnings.
MEMS Journal: How does your LIDAR technology work?  And how does it measure up to other competing alternatives in terms of performance and cost?    

Jari Honkanen: For LIDAR applications we use our scanning MEMS mirror, but instead of visible light laser diodes, we utilize one or several invisible near infrared (IR) laser diodes.  The IR beam is reflected onto the biaxial MEMS scanning mirror that scans the beam in a raster pattern.  Our LIDAR system also contains an IR photodetector that will detect reflections from the scanner IR laser beam.  Since speed of light is constant and we know the time when we emit the specific laser pulse and when we receive the reflection back, we can calculate the distance to the object that the light reflected back from.

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