The project aims to improve the indoor positioning of mobile robots using a new method that adaptively adjusts the uncertainty of lidar measurements in an extended Kalman filter (EKF) to improve positioning accuracy, especially in ever-changing, dynamic environments.
Technologies: Robotics, Robot Operating System (ROS2), Extended Kalman filter (EKF), LiDAR
The development and initial tests of the method have been completed. Final testing will be carried out in 2025. The method developed uses photo radar to identify environmental features from the point clouds created. These are compared with a 3D map of the space generated by a Kalman filter, whose uncertainty is continuously adjusted between measurements. Aalto University has provided both the facilities and a mobile robot for testing.
Project outcome
The method developed in the project increased the positioning accuracy in different test scenarios compared to the standard EKF, showing resilience to environmental changes and sudden movements. The developed positioning method significantly improves the positioning reliability of mobile robots in dynamic environments.
Mitsubishi Logisnext Europe Ltd
Mitsubishi Logisnext Europe Ltd designs, manufactures and supplies high-tech logistics solutions including a wide range of forklifts, automation systems and related solutions and services.