Object Detection for Autonomous Guided Vehicle

Tanmay Bhosale, Ajim Attar, Prathamesh Warang, Randhir Patil


In recent years camera networks have been widely used in several applications such as surveillance, video conferencing, etc. The autonomous vehicle can reduce critical fatalities and injuries. Thus, an autonomous vehicle is the solution to this eliminating the possibility of human error and drastically changing the danger associated with the motor. In the rural environment, a lack of accuracy and estimation of the vehicle can be observed since the roads are not well constructed, however, in an urban area, it is very easy to detect landmarks on roads. The joint observation model is used for compensating the error of individual observations and the state of the vehicle. The purpose of this paper is to present the design of an obstacle detection system using LIDAR for an autonomous guided vehicle. LIDAR is mostly used in an autonomous vehicle to detect obstacles. It provides the exact location of obstacles in front of the vehicle. The main motto of using the LIDAR camera is to detect obstacles and send data to the controller. The Observational-Experimental methodology was used for this research. It controls the speed of the vehicle, emergency braking when an object is being detected. An autonomous vehicle system with LIDAR can be used on one-way or two-way roads and it is widely used for industrial purposes. The autonomous vehicle is useful for one-way or two-way roads. The aim of the obstacle detection system is it reduces accidents on road and reduce human power.


Autonomous Guided Vehicle; Obstacle Detection; LIDAR

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Ashok, W. R., Panse, M. S., and Apte, H. (2015). Laser triangulation-based object height measurement. International Journal for Research in Emergency Science and Technology, 2, 61-67.

Bhangale, M., Dabhade, G., Khairnar, A., and Bhagat, M. (2016). Self-driving car to demonstrate real time obstacles & object detection. The Indonesian Journal of Education Research and Technology (IRJET), 3(11), 2395-0056.

Kewate, S. R., Karmare, S. V., Sayankar, N., and Gavhale, S. (2014). Automatic Speed Control System by the Color Sensor for Automobiles–An Innovative Model Based Approach. International Journal of Advanced Mechanical Engineering, 4(2), 223-230.

Naseri, A., and Azmoon, O. (2011). Evaluation of data fusion in radars network and determination of optimum algorithm. International Journal of UbiComp, 2(4), 51.


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