4 ms·

The sensor fusion reminds me of the F-35 JSF. The software seems to be one of the big things in the fighter project. So actually this might be a good fit for G

The sensor fusion reminds me of the F-35 JSF. The software seems to be one of the big things in the fighter project. So actually this might be a good fit for Google after all. Sensors are getting trivialized. I'm sure Google is working for a LIDARless car. They've published their stereo vision to 3d library. https://code.google.com/p/openvis3d/ https://code.google.com/p/openvis3d/

vonmoltke 12y ago
Indeed. This is a sensor fusion problem I really want to work on. I loved the problem space while I was working for Raytheon, but I can't stand working on large government programs. I'm surprised about the lack of IR sensors, though. I can think of cases where the IR data could be fused with data from other sensors, particularly visual, to improve object recognition. Particularly pedestrian and animal detection.
- toomuchtodo 12y ago
  > Indeed. This is a sensor fusion problem I really want to work on. Have you thought about working for Tesla? autopilot@teslamotors.com
  - vonmoltke 12y ago
    I have, actually. I'm concerned about the work-life balance there, though.
    - toomuchtodo 12y ago
      Same reason I don't work in IT at SpaceX. I wouldn't have a wife anymore.
krasin 12y ago
I should point out that openvis3d is relatively old news (2006-2007).
- benjamincburns 12y ago
  Would you care to share some of the new news? I'm presently looking for computationally efficient dense monocular VSLAM (visual simultaneous localisation and mapping) implementations to use in an upcoming personal project. openvis3d looks like it could be used to do binocular VSLAM, which would also be acceptable. To seed the conversation, LSD-SLAM [1] looks really interesting, but last I checked the source has not yet been released. By "interesting" I mean that it's real time, dense, and runs on a low-powered (smart phone) CPU. I wish it was accurate enough to not need loop closure, but it's the best I was able to find over an afternoon of searching. 1: http://vision.in.tum.de/research/lsdslam http://vision.in.tum.de/research/lsdslam
  - krasin 12y ago
    I find https://github.com/uzh-rpg/rpg_svo https://github.com/uzh-rpg/rpg_svo very promising. It's not exactly the same thing, though. See their video: https://www.youtube.com/watch?v=2YnIMfw6bJY https://www.youtube.com/watch?v=2YnIMfw6bJY
    - Gravityloss 12y ago
      That looks very good. There are a lot of uses for SLAM and I hope the technology gets out of the labs soon. (My uses would be man portable indoor mapping of very complex structures with relatively good accuracy.)

vonmoltke 12y ago

Indeed. This is a sensor fusion problem I really want to work on. I loved the problem space while I was working for Raytheon, but I can't stand working on large government programs. I'm surprised about the lack of IR sensors, though. I can think of cases where the IR data could be fused with data from other sensors, particularly visual, to improve object recognition. Particularly pedestrian and animal detection.

toomuchtodo 12y ago
> Indeed. This is a sensor fusion problem I really want to work on. Have you thought about working for Tesla? autopilot@teslamotors.com
- vonmoltke 12y ago
  I have, actually. I'm concerned about the work-life balance there, though.
  - toomuchtodo 12y ago
    Same reason I don't work in IT at SpaceX. I wouldn't have a wife anymore.

krasin 12y ago

I should point out that openvis3d is relatively old news (2006-2007).

benjamincburns 12y ago
Would you care to share some of the new news? I'm presently looking for computationally efficient dense monocular VSLAM (visual simultaneous localisation and mapping) implementations to use in an upcoming personal project. openvis3d looks like it could be used to do binocular VSLAM, which would also be acceptable. To seed the conversation, LSD-SLAM [1] looks really interesting, but last I checked the source has not yet been released. By "interesting" I mean that it's real time, dense, and runs on a low-powered (smart phone) CPU. I wish it was accurate enough to not need loop closure, but it's the best I was able to find over an afternoon of searching. 1: http://vision.in.tum.de/research/lsdslam http://vision.in.tum.de/research/lsdslam
- krasin 12y ago
  I find https://github.com/uzh-rpg/rpg_svo https://github.com/uzh-rpg/rpg_svo very promising. It's not exactly the same thing, though. See their video: https://www.youtube.com/watch?v=2YnIMfw6bJY https://www.youtube.com/watch?v=2YnIMfw6bJY
  - Gravityloss 12y ago
    That looks very good. There are a lot of uses for SLAM and I hope the technology gets out of the labs soon. (My uses would be man portable indoor mapping of very complex structures with relatively good accuracy.)