Chapter 4.2 – A Side of Data with My Robot1

The consideration of data set design, collection, and distribution methodology is becoming increasingly important as robots move out of fully controlled settings, such as assembly lines, into unstructured environments. Extensive knowledge bases and data sets will potentially offer a means of coping with the variability inherent in the real world. In this study, we introduce three new data sets related to mobile manipulation in human environments. The first set contains a large corpus of robot sensor data collected in typical office environments. Using a crowd-sourcing approach, this set has been annotated with ground-truth information outlining people in camera images. The second data set consists of three-dimensional (3-D) models for a number of graspable objects commonly encountered in households and offices. Using a simulator, we have identified on each of these objects a large number of grasp points for a parallel jaw gripper. This information has been used to attempt a large number of grasping tasks using a real robot. The third data set contains extensive proprioceptive and ground truth information regarding the outcome of these tasks