Development of advanced virtual collaborative multi-vehicle simulation platform

• Main Author: Toh, Teow Ghee
• Other Authors: Xie Lihua
• Format: Theses and Dissertations
• Language: English
• Published: 2013
• Subjects: DRNTU::Engineering::Electrical and electronic engineering
• Online Access: https://hdl.handle.net/10356/51107
• Institution: Nanyang Technological University

Setting up a hardware platform for multi-vehicle cooperation can be very complex, and resource and time consuming. Factors like vehicle dynamics and operating environment would affect the performance and need to be handled as well. Part of the purpose of this research is to develop a virtual platform that allows user to overcome these problems to test their algorithms without the need of setting up the real hardware. This virtual platform must have similar performance with the algorithm running in the real world and allows easy porting as well. The scope of work would include use of sensors for localization and collision avoidance, wireless communications for information exchanges, firmware and software programming for implementing control algorithms, etc. With the virtual platform, the second major part of the work here is to implement formation and search control in this platform and address all the underlying difficulties. There are two underlying difficulty areas being identified here. The first is to ensure that the performance is close to that in the real world. As the implementation involves a number of algorithms, formation control, search control, obstacle avoidance, tracking and pattern recognition, some of the algorithms would compete between each other for the kinematics control of the vehicle. Thus the second difficulty here is to focus on strategies of switching between algorithms to allow smoother taking over during operations. There are more focused efforts being spent here on the switching between formation and obstacle avoidance, as it conventionally occupies the vast majority of the kinematics control. This research presents an obstacle avoidance algorithm that is based on logical understanding of the surrounding, and adaptively allows multi-vehicle to change formation on a real-time basis.