scholarly journals An INS-UWB Based Collision Avoidance System for AGV

Algorithms ◽  
2019 ◽  
Vol 12 (2) ◽  
pp. 40 ◽  
Author(s):  
Shunkai Sun ◽  
Jianping Hu ◽  
Jie Li ◽  
Ruidong Liu ◽  
Meng Shu ◽  
...  
Keyword(s):  
Collision Avoidance ◽  
Wide Band ◽  
Position Estimation ◽  
Localization Accuracy ◽  
Laser Guiding ◽  
Current Location ◽  
Anchor Nodes ◽  
Accurate Position ◽  
Environmental Requirements ◽  
Collision Avoidance System

As a highly automated carrying vehicle, an automated guided vehicle (AGV) has been widely applied in various industrial areas. The collision avoidance of AGV is always a problem in factories. Current solutions such as inertial and laser guiding have low flexibility and high environmental requirements. An INS (inertial navigation system)-UWB (ultra-wide band) based AGV collision avoidance system is introduced to improve the safety and flexibility of AGV in factories. An electronic map of the factory is established and the UWB anchor nodes are deployed in order to realize an accurate positioning. The extended Kalman filter (EKF) scheme that combines UWB with INS data is used to improve the localization accuracy. The current location of AGV and its motion state data are used to predict its next position, decrease the effect of control delay of AGV and avoid collisions among AGVs. Finally, experiments are given to show that the EKF scheme can get accurate position estimation and the collisions among AGVs can be detected and avoided in time.

scholarly journals Effects of the Body Wearable Sensor Position on the UWB Localization Accuracy

2019 ◽  
Author(s):  
Timothy Otim ◽  
Luis Enrique Díez ◽  
Alfonso Bahillo ◽  
Peio Lopez Iturri ◽  
Francisco Falcone
Keyword(s):  
Head Position ◽  
Position Estimation ◽  
The Body ◽  
Wearable Sensor ◽  
Sensor Location ◽  
Localization Accuracy ◽  
Sensor Position ◽  
Accurate Position ◽  
Sensor Positions ◽  
Localization Systems

In recent years, several Ultrawideband (UWB) localization systems have already been proposed and evaluated for accurate position estimation of pedestrians. However, most of them are evaluated for a particular wearable sensor position; hence the accuracy obtained is subject to a given wearable sensor position. In this paper, we study the effects of body wearable sensor positions i.e., chest, arm, ankle, wrist, thigh, fore-head, hand, on the localization accuracy. The conclusion drawn is that the fore-head is the best, and the chest is the worst body sensor location for tracking a pedestrian. While the fore-head position is able to set an error lower than 0.35 m (90th percentile), the chest is able to set 4 m. The reason for such a contrast in the performance lies in the fact that in NLOS situations, the chest as an obstacle is larger in size and thickness than any other part of the human body, which the UWB signal needs to overcome to reach the target wearable sensor. And so, the large errors arise due to the signal arriving at the target wearable sensor from reflections of a nearby object or a wall in the environment.

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