Autonomous humanoid navigation using laser and odometry data

Abstract

In this paper we present a novel approach to legged humanoid navigation on indoor environments using classical probabilistic SLAM methods based on odometry information and laser measurements. We use two small lasers installed in the robot feet to capture distance data. Odometry is obtained by calculating the position of each laser-foot at every time step. The SLAM problem is solved by using a multi-laser SLAM solution together with a holonomic motion model. Navigation skills also include a path planning module with obstacle avoidance for autonomous navigation in indoor environments. The whole process is performed within the robot itself. Optionally, localization robustness is increased by adding the detection of landmarks using a camera. Results obtained are presented for the 1.5 m tall Reem-B humanoid robot.