Real-time 3D simultaneous localization and map-building for a dynamic walking humanoid robot

Abstract

In this paper, we develop an onboard real-time 3D visual simultaneous localization and mapping system for a dynamic walking humanoid robot. With the constraints of processing and real-time operation, the system uses a lightweight localization and mapping approach based around the well-known extended Kalman filter but that features a robust and real-time relocalization system able to allow loop-closing and robust localization in 6D. The robot is controlled by torque references at the joints using its dynamic properties. This results in more energy efficient motion but also in lager movement than the one found in a conventional ZMP-based humanoid which carefully maintains the position of the center of mass on the plane. These more agile motions pose challenges for a visual mapping system having to operate in real time. The developed system features a combination of stereo camera, robust visual descriptors, and motion model switching to compensate for the larger motion and uncertainty. We provide practical implementation details of the system and methods, and test on the real humanoid robot. We compare our results with motion obtained with a motion capture system.