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Author here :) LIDAR itself is just a sensor, it does not process the data nor does it output a directly usable image like a camera more or less does. LIDAR in

Author here :) LIDAR itself is just a sensor, it does not process the data nor does it output a directly usable image like a camera more or less does. LIDAR in this case is a rotating laser and while it scans, the vehicle moves (imagine moving a paper when a copier scans it). All processing is done later, first to construct an image and then to understand and use it. Part of why I wrote the piece was to explain how things can go wrong even if your LIDAR works fine.

wnoise 9y ago
You don't have to "construct an image" to use LIDAR returns. Minimal processing on the point cloud will tell you that there's an obstacle, and you don't need more than that to start trying to avoid hitting it. A simple occupancy grid map, for instance, would suffice. https://en.wikipedia.org/wiki/Occupancy_grid_mapping https://en.wikipedia.org/wiki/Occupancy_grid_mapping
- nabla9 9y ago
  The problem with naive occupancy grid mapping from sparse LIDAR data is that things like birds, falling leaves, pieces of paper of plastic bags flying in the wind can mark the grid occupied. Emergency breaking for all these cases would be very dangerous. The same object must be scanned multiple times to get the idea if the object is something to be avoided.
  - wnoise 9y ago
    Quite true -- but LIDAR has a very high refresh rate, and it's not hard to do better than naive grid mapping. This was a full height pedestrian plus bicycle, which would have multiple nice returns from a Velodyne HDL 64 at these distances.
  - smileysteve 9y ago
    Birds, plastic bags, cardboard boxes, small pieces of wood, and pieces of tires are perfectly good reasons to apply brakes and drive with caution to avoid.
rasz 9y ago
and yet you wrote "now one of them thinks it’s a dog" as if sensors did image classification.
- 8note 9y ago
  all kinds of things can learn to think things are dogs. you don't need an image

wnoise 9y ago

You don't have to "construct an image" to use LIDAR returns. Minimal processing on the point cloud will tell you that there's an obstacle, and you don't need more than that to start trying to avoid hitting it. A simple occupancy grid map, for instance, would suffice. https://en.wikipedia.org/wiki/Occupancy_grid_mapping https://en.wikipedia.org/wiki/Occupancy_grid_mapping

nabla9 9y ago
The problem with naive occupancy grid mapping from sparse LIDAR data is that things like birds, falling leaves, pieces of paper of plastic bags flying in the wind can mark the grid occupied. Emergency breaking for all these cases would be very dangerous. The same object must be scanned multiple times to get the idea if the object is something to be avoided.
- wnoise 9y ago
  Quite true -- but LIDAR has a very high refresh rate, and it's not hard to do better than naive grid mapping. This was a full height pedestrian plus bicycle, which would have multiple nice returns from a Velodyne HDL 64 at these distances.
- smileysteve 9y ago
  Birds, plastic bags, cardboard boxes, small pieces of wood, and pieces of tires are perfectly good reasons to apply brakes and drive with caution to avoid.

rasz 9y ago

and yet you wrote "now one of them thinks it’s a dog" as if sensors did image classification.

8note 9y ago
all kinds of things can learn to think things are dogs. you don't need an image