Open AccessLeader-Follower Tracking System for Agricultural Vehicles: Fusion of Laser and Odometry Positioning Using Extended Kalman Filter
Author(s) -
Zhang Lin Huan,
Tomohiro Takigawa,
Tofael Ahamed
Publication year - 2015
Publication title -
international journal of robotics and automation (ijra)/iaes international journal of robotics and automation
Language(s) - English
Resource type - Journals
eISSN - 2722-2586
pISSN - 2089-4856
DOI - 10.11591/ijra.v4i1.pp1-18
Subject(s) - extended kalman filter , tracking (education) , tracking system , heading (navigation) , kalman filter , control theory (sociology) , odometry , computer vision , computer science , artificial intelligence , position (finance) , stability (learning theory) , robot , engineering , mobile robot , control (management) , psychology , pedagogy , finance , machine learning , economics , aerospace engineering
The aim of this research was to develop a safe human-driven and autonomous leader-follower tracking system for an autonomous tractor. To enable the tracking system, a laser range finder (LRF)-based landmark detection system was designed to observe the relative position between a leader and a follower used in agricultural operations. The virtual follower-based formation-tracking algorithm was developed to minimize tracking errors and ensure safety. An extended Kalman filter (EKF) was implemented for fusing LRF and odometry position to ensure stability of tracking in noisy farmland conditions. Simulations were conducted for tracking the leader in small and large sinusoidal curved paths. Simulated results verified high accuracy of formation tracking, stable velocity, and regulated steering angle of the follower. The tracking method confirmed the follower could follow the leader with a required formation safely and steadily in noisy conditions. The EKF helped to improve observation accuracy, velocity, and steering angle stability of the follower. As a result of the improved accuracy of observation and motion action, the tracking performance for lateral, longitudinal, and heading were also improved after the EKF was implemented in the tracking system.