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Processing of LiDAR and IMU data for target detection and odometry of a mobile robot

Giannoccaro Nicola Ivan, Nishida Takeshi, Lay-Ekuakille Aimé, Velazquez Ramiro, Visconti Paolo

Journal of Automation Mobile Robotics and Intelligent Systems

2022

Vol. 16, No. 1

3--13

In this paper, the processing of the data of a 3D light detection and distance measurement (LiDAR) sensor mounted on a mobile robot is demonstrated, introducing an innovative methodology to manage the data and extract useful information. The LiDAR sensor is placed on a mobile robot which has a modular design that permits the easy change of the number of wheels, was designed to travel through several environments, and saves energy by changing the number and arrangement of the wheels in each environment. In addition, the robot can recognize landmarks in a structured environment by using a classification technique on each frame acquired by the LiDAR. Furthermore, considering the experimental tests, a new simple algorithm based on the LiDAR data processing together with the inertial data (IMU sensor) through a Kalman filter is proposed to characterize the robot’s pose by the surrounding environment with fixed landmarks. Finally, the limits of the proposed algorithm have been analyzed, highlighting new improvements in the future prospective development for permitting autonomous navigation and environment perception with a simple, modular, and low-cost device.

Analysis of the surrounding environment using an innovative algorithm based on lidar data on a modular mobile robot

Giannoccaro Nicola Ivan, Nishida Takeshi

Journal of Automation Mobile Robotics and Intelligent Systems

2020

Vol. 14, No. 4

25--34

In this paper, a low cost mobile robot with a modular design that permits the easy change of the number of wheels is considered for generation of 3D digital maps by using ROS tools and a 3D light detection and distance measurement (LiDAR) sensor. The modular robot is thought for travelling through several environments with saving the energy by changing the number and arrangement of the wheels according to the environment. The presented robot can construct a 3D map in particular structured environment and the running performance was investigated by an extensive characterization. Furthermore, in light of the experimental tests, a new simple algorithm based exclusively of the processing of the LiDAR data is proposed with the aim of characterizing the surrounding environment with fixed landmarks and mobile targets. Finally, the limits of this prototype and of the proposed algorithm have been analyzed, highlighting new improvements in the future perspective development for permitting an autonomous environment perception with a simple, modular and low-cost device.