Abstract

Accurate positioning is a requirement for many applications, including safety-critical autonomous vehicles. To reduce cost and at the same time improving accuracy for positioning of autonomous vehicles, new methods, tools, and research platforms are needed. We have created a low-cost testbed consisting of electronics and software that can be fitted on model vehicles allowing them to follow trajectories autonomously with a position accuracy of around 3 cm outdoors. The position of the vehicles is derived from sensor fusion between Real-Time Kinematic Satellite Navigation (RTK-SN), odometry, and inertial measurement and performs well within a 10 km radius from a base station. Trajectories to be followed can be edited with a custom GUI, where also several model vehicles can be controlled and visualized in real time. All software and Printed Circuit Boards (PCBs) for our testbed are available as open source to make customization and development possible. Our testbed can be used for research within autonomous driving, for carrying test equipment, and other applications where low cost and accurate positioning and navigation are required.

Highlights

  • It is common to use model cars for automotive research, and several studies are published in that field

  • The authors describe high level algorithms for handling different traffic scenarios that can be used given access to a model vehicle that can follow trajectories. While these projects are an aid in education and research about autonomous driving, a significant amount of work is still required from the researchers or students to get a self-driving model car up and Journal of Robotics running

  • Our testbed consists of a control Printed Circuit Board (PCB) we have developed that can be connected to a VESC open-source motor controller over Controller Area Network- (CAN-) bus

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Summary

Introduction

It is common to use model cars for automotive research, and several studies are published in that field. Model cars have been used to develop obstacle avoidance algorithms for mobile robots [3] and in student projects to teach them about autonomous driving [4] These projects are specific and aimed at certain tasks, and the hardware and software are not available to replicate for use within other areas. The authors describe high level algorithms for handling different traffic scenarios that can be used given access to a model vehicle that can follow trajectories While these projects are an aid in education and research about autonomous driving, a significant amount of work is still required from the researchers or students to get a self-driving model car up and Journal of Robotics running.

Architecture Overview
Positioning
Trajectory Following
Conclusion
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