Trajectory Planning for Nonholonomic Mobile Robot Using Extended Kalman Filter

Abstract

In the mobile robotic systems, a precise estimate of the robot pose with the intention of the optimization in the path planning is essential for the correct performance, on the part of the robots, for tasks that are destined to it. This paper describes the use of RF digital signal interacting with beacons for computational triangulation in the way to provide a pose estimative at bidimensional indoor environment, where GPS system is out of range. This methodology takes advantage of high‐performance multicore DSP processors to calculate ToF of the order about ns. Sensors data like odometry, compass, and the result of triangulation Cartesian estimative, are fused for better position estimative. It uses a mathematical and computational tool for nonlinear systems with time‐discrete sampling for pose estimative calculation of mobile robots, with the utilization of extended Kalman filter (EKF). A mobile robot platform with differential drive and nonholonomic constraints is used as a base for state space, plants and measurements models that are used in the simulations and validation of the experiments.