3 ms·
I know that there's a lot of successful work in specific controlled environments (company X's factory floor), and that a lot of environment understanding/SLAM i
by heyitsguay 6y ago
I know that there's a lot of successful work in specific controlled environments (company X's factory floor), and that a lot of environment understanding/SLAM is broadly unsolved in arbitrary uncontrolled environments, but what about specific uncontrolled environments? What if i want a beer serving robot to learn a consistent, high-accuracy model of just my house, the way it is, and I'm willing to put in some technical work? Can i do any better than completely hand crafting a 3D object model or similar?
- cpgxiii 6y agoIf you have high-quality 3D sensors (or in some cases, good-enough 2D cameras) and usable IMU/odometry, you can assemble quite reasonable 3D models for many small environments. The biggest challenges in a home environment are that many items we want in our houses (stainless steel appliances, chairs with thin legs, glass anything, reflective floor materials) are almost pathologically bad from a computer vision standpoint and are very hard to see and avoid in an uncontrolled household setting. Vision-based navigation against a known environment is doable with reasonable reliability, but adding fixed markers or positioning systems goes a long way towards robustness.
- redis_mlc 6y agoWillow Garage sold a robot that did that. Only $440,000 each. It was a vanity project of the Google founders/early employees, but they contributed to ROS (the Robot Operating System.) https://en.wikipedia.org/wiki/Willow_Garage https://en.wikipedia.org/wiki/Willow_Garage https://en.wikipedia.org/wiki/Robot_Operating_System https://en.wikipedia.org/wiki/Robot_Operating_System