Challenges for Lidar Software

In an interview, Anand Gopalan, CEO of Velodyne Lidar, Inc. (San Jose, CA), discussed lidar software for ADAS and autonomous vehicles. Primary goals are to increase the speed of response and optimize efficient use of computational resources. Another important challenge is what he calls the tyranny of corner cases for autonomous vehicles — for example, a taxi pulling back into traffic after dropping a passenger at the curb. Then there’s the problem of near-field sensing — say a bicyclist alongside a turning vehicle or a ball rolling into the street. These kinds of situations require software to provide improved classification of objects and prediction of behavior. This raises the question of where to use artificial intelligence vs deterministic algorithms.