Position estimation of selected targets

Recovering depth and 3D position using known camera motion is useful for solving many problems in robotics such as object manipulation, navigation, and localization. Most existing techniques attempt to solve the general problem by recovering depth across the entire image. They oftentimes make linear dynamics assumptions or use poorly recoverable metrics such as optical flow. An estimation technique is presented that retains the nonlinear camera dynamics and provides an accurate 3D position estimate of selected targets within the environment. In practice, the technique is accurate enough to fully specify the placement of a gripper for object manipulation after forward (as opposed to lateral) movement of a single camera. The technique also provides probabilistic information regarding the estimate, which can be used to make intelligent, informed decisions. We employed this technique at the 1995 AAAI robot competition where our robot, Lola, placed 1st in Office Clean-up where it was able to pick up trash and recyclables and deposit them in the appropriate receptacles with great success. Results of our implementation on Lola are also presented