Augmentation of Mapping and Autonomous Navigation for Hexapod Robots by using a Visual Inertial System

Abstract

Abstract In our previous work, we focused on the development of Razbot, a hexapod platform, and achieving its autonomy using the Robot Operating System (ROS). Therein, we also explained the difficulties faced with Razbot while trying to execute complex operations autonomously. Hence, in this work we address the problem and make an attempt at improving the odometry measurements of Razbot by introducing a Visual Inertial System (VIS) that includes a pair of synchronized monocular camera and inertial measurement unit which makes it capable of mapping the environment and autonomously navigating in it with increased effectiveness. To introduce the VIS, we made minor modifications in the components used and the control scheme of Razbot. In this work, we take help of the Extended Kalman Filter (EKF) for the fusion of odometry sources. Further, we also analyse the accuracy of the fused odometry by comparing the same and evaluating the errors or drifts in odometry before and after introducing the VIS in Razbot. Based on these results, we make a conclusion that the odometry source from VIS can significantly lower errors and drifts in fused odometry data, thus improving autonomous navigation and mapping of the hexapod robot. The implementation of this system will allow Razbot to be used in even more varied applications than those specified earlier.