A 3D positioning system for off-road autonomous vehicles

Autonomous vehicles need accurate and dependable positioning, and these systems need to be tested extensively. We have evaluated positioning based on ultrawideband (UWB) ranging with our self-driving model car using a highly automated approach. Random drivable trajectories were generated, while the UWB position was compared against the Real-Time Kinematic Satellite Navigation (RTK-SN) positioning system which our model car also is equipped with. Fault injection was used to study the fault tolerance of the UWB positioning system. Addressed challenges are automatically generating test cases for real-time hardware, restoring the state between tests, and maintaining safety by preventing collisions. We were able to automatically generate and carry out hundreds of experiments on the model car in real time and rerun them consistently with and without fault injection enabled. Thereby, we demonstrate one novel approach to perform automated testing on complex real-time hardware.

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Accuracy Considerations in a 3-D Ultrasonic Positioning System Based on the Difference in Time of Flights

Journal of Dynamic Systems Measurement and Control ◽

10.1115/1.1514057 ◽

2002 ◽

Vol 124 (4) ◽

pp. 688-693 ◽

Cited By ~ 2

Author(s):

Nishant Unnikrishnan ◽

Probir Kumar Ray ◽

Ajay Mahajan ◽

Tsuchin Chu

Keyword(s):

Precision Measurement ◽

Autonomous Vehicles ◽

Vibration Analysis ◽

Arrival Time ◽

Wave Theory ◽

Positioning System ◽

Multiple Receivers ◽

Critical Issues ◽

Measurement Devices ◽

The Difference

This paper presents a method to improve the accuracy of an ultrasonic 3-D positioning system that uses the differences in the time of flights from a single transmitter to multiple receivers. The paper presents techniques to overcome errors in ultrasonic systems due to critical issues such as misalignment of transducers, changes in the speed of sound, arrival time of signals, etc. Further, the work presented here is not just applicable to ultrasonic systems but to all systems based on wave theory. This work will impact applications in robotics, virtual reality, precision measurement devices and probes, guidance of autonomous vehicles, and vibration analysis.

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Precise Positioning of Autonomous Vehicles Combining UWB Ranging Estimations with On-Board Sensors

Electronics ◽

10.3390/electronics9081238 ◽

2020 ◽

Vol 9 (8) ◽

pp. 1238

Author(s):

Javier San Martín ◽

Ainhoa Cortés ◽

Leticia Zamora-Cadenas ◽

Bo Joel Svensson

Keyword(s):

Autonomous Vehicles ◽

Research Work ◽

Ultra Wideband ◽

Line Of Sight ◽

Use Case ◽

Positioning System ◽

Precise Positioning ◽

Research Institutes ◽

Simulated Environment ◽

Non Line Of Sight

In this paper, we analyze the performance of a positioning system based on the fusion of Ultra-Wideband (UWB) ranging estimates together with odometry and inertial data from the vehicle. For carrying out this data fusion, an Extended Kalman Filter (EKF) has been used. Furthermore, a post-processing algorithm has been designed to remove the Non Line-Of-Sight (NLOS) UWB ranging estimates to further improve the accuracy of the proposed solution. This solution has been tested using both a simulated environment and a real environment. This research work is in the scope of the PRoPART European Project. The different real tests have been performed on the AstaZero proving ground using a Radio Control car (RC car) developed by RISE (Research Institutes of Sweden) as testing platform. Thus, a real time positioning solution has been achieved complying with the accuracy requirements for the PRoPART use case.

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Low-Cost Receiver and Network Real-Time Kinematic Positioning for use in Connected and Autonomous Vehicles

Journal of Navigation ◽

10.1017/s037346331800111x ◽

2019 ◽

Vol 72 (04) ◽

pp. 917-930

Author(s):

Fang-Shii Ning ◽

Xiaolin Meng ◽

Yi-Ting Wang

Keyword(s):

Real Time ◽

Autonomous Vehicles ◽

High Performance ◽

Low Cost ◽

Satellite System ◽

High Accuracy ◽

Future Trend ◽

Intelligent Transport System ◽

Positioning System ◽

Gnss Receiver

Connected and Autonomous Vehicles (CAVs) have been researched extensively for solving traffic issues and for realising the concept of an intelligent transport system. A well-developed positioning system is critical for CAVs to achieve these aims. The system should provide high accuracy, mobility, continuity, flexibility and scalability. However, high-performance equipment is too expensive for the commercial use of CAVs; therefore, the use of a low-cost Global Navigation Satellite System (GNSS) receiver to achieve real-time, high-accuracy and ubiquitous positioning performance will be a future trend. This research used RTKLIB software to develop a low-cost GNSS receiver positioning system and assessed the developed positioning system according to the requirements of CAV applications. Kinematic tests were conducted to evaluate the positioning performance of the low-cost receiver in a CAV driving environment based on the accuracy requirements of CAVs. The results showed that the low-cost receiver satisfied the “Where in Lane” accuracy level (0·5 m) and achieved a similar positioning performance in rural, interurban, urban and motorway areas.

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Kinematic and Dynamic Vehicle Model-Assisted Global Positioning Method for Autonomous Vehicles with Low-Cost GPS/Camera/In-Vehicle Sensors

Sensors ◽

10.3390/s19245430 ◽

2019 ◽

Vol 19 (24) ◽

pp. 5430 ◽

Cited By ~ 7

Author(s):

Haigen Min ◽

Xia Wu ◽

Chaoyi Cheng ◽

Xiangmo Zhao

Keyword(s):

Coordinate System ◽

Autonomous Vehicles ◽

Low Cost ◽

Positioning System ◽

Visual Slam ◽

Multiple Model ◽

Positioning Systems ◽

Local Accuracy ◽

Global Positioning ◽

Vehicle Sensors

Real-time, precise and low-cost vehicular positioning systems associated with global continuous coordinates are needed for path planning and motion control in autonomous vehicles. However, existing positioning systems do not perform well in urban canyons, tunnels and indoor parking lots. To address this issue, this paper proposes a multi-sensor positioning system that combines a global positioning system (GPS), a camera and in-vehicle sensors assisted by kinematic and dynamic vehicle models. First, the system eliminates image blurring and removes false feature correspondences to ensure the local accuracy and stability of the visual simultaneous localisation and mapping (SLAM) algorithm. Next, the global GPS coordinates are transferred to a local coordinate system that is consistent with the visual SLAM process, and the GPS and visual SLAM tracks are calibrated with the improved weighted iterative closest point and least absolute deviation methods. Finally, an inverse coordinate system conversion is conducted to obtain the position in the global coordinate system. To improve the positioning accuracy, information from the in-vehicle sensors is fused with the interacting multiple-model extended Kalman filter based on kinematic and dynamic vehicle models. The developed algorithm was verified via intensive simulations and evaluated through experiments using KITTI benchmarks (A project of Karlsruhe Institute of Technology and Toyota Technological Institute at Chicago) and data captured using our autonomous vehicle platform. The results show that the proposed positioning system improves the accuracy and reliability of positioning in environments in which the Global Navigation Satellite System is not available. The developed system is suitable for the positioning and navigation of autonomous vehicles.

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