LIDAR Scan
2019
We use the same technology that prevents self-driving cars from slamming into canyon walls painted to look like a tunnel in order to map physical environments for a more accurate AR experience. We love this. Coyotes (carnivorous vulgaris) of the obsessive, sociopathic variety do not.
![](https://cdn.sanity.io/images/uk7b627p/production/8267da276d614f67483e153bf0aa31e4073242dc-2048x1141.png?w=600&q=95&auto=format)
As impressive as mobile SLAM technology is, even the best versions of it model the world as though it were quickly sculpted in wax and left out on a summer day. And that won’t cut the mustard.
![](https://cdn.sanity.io/images/uk7b627p/production/ae1a5a89aef20f3df38af35b2e67e4dc87f9df23-1368x1268.png?w=600&q=95&auto=format)
LIDAR scanning lets us capture environments with enough detail that we can animate a ball bouncing down the stairs and trust that the user will see the ball hit the exact step we intend.
![](https://cdn.sanity.io/images/uk7b627p/production/36c72a26bcdc6a22dcbea02b5cf9471fb6061746-2048x1139.png?w=600&q=95&auto=format)
We imported and calibrated the data in Autodesk Recap, a tool used in the Architectural and Engineering industries. Then we optimized the dataset in the open source software Cloud Compare and exported it as a .PLY. Our CT team wrote a python script to import the data into Cinema 4-D, and rebuilt the environment as a low-polygon model that was used as a template for our animators. Next, we wrote a series of custom animation processing and export tools to allow for hundreds of dynamic balls and animations.
![](https://cdn.sanity.io/images/uk7b627p/production/6f37dd2934976b0932eaa5ca58501a2f3ecfd5be-2074x1166.png?w=600&q=95&auto=format)
Advertisements have been promising experiences like this as the future of mobile AR for years. It was exciting to see it running on consumer phones, and to know that we’re a significant step closer to the delight of world-aware AR being available to everyone. Even coyotes.