TY  - JOUR
AB  - Landmark‐based navigation of autonomous mobile robots or vehicles has been widely adopted in industry. Such a navigation strategy relies on identification and subsequent recognition of distinctive environment features or objects that are either known a priori or extracted dynamically. This process has inherent difficulties in practice due to sensor noise and environment uncertainty. This paper is to propose a navigation algorithm that simultaneously locates the robots and updates landmarks in a manufacturing environment. A key issue being addressed is how to improve the localization accuracy for mobile robots in a continuous operation, in which the Kalman filter algorithm is adopted to integrate odometry data with scanner data to achieve the required robustness and accuracy. The Kohonen neural networks have been used to recognize landmarks using scanner data in order to initialize and recalibrate the robot position by means of triangulation when necessary.
VL  - 27
IS  - 6
SN  - 0143-991X
DO  - 10.1108/01439910010378879
UR  - https://doi.org/10.1108/01439910010378879
AU  - Hu Huosheng
AU  - Gu Dongbing
PY  - 2000
Y1  - 2000/01/01
TI  - Landmark‐based navigation of industrial mobile robots
T2  - Industrial Robot: An International Journal
PB  - MCB UP Ltd
SP  - 458
EP  - 467
Y2  - 2024/04/19
ER  -