Experimental analysis of a low-cost dead reckoning navigation system for a land vehicle using a robust AHRS

Dams are important engineering facilities in the water conservancy industry. They have many functions, such as flood control, electric power generation, irrigation, water supply, shipping, etc. Therefore, their long-term safety is crucial to operational stability. Because of the complexity of the dam environment, robots with various kinds of sensors are a good choice to replace humans to perform a surveillance job. In this paper, an autonomous system design is proposed for dam ground surveillance robots, which includes general solution, electromechanical layout, sensors scheme, and navigation method. A strong and agile skid-steered mobile robot body platform is designed and created, which can be controlled accurately based on an MCU and an onboard IMU. A novel low-cost LiDAR is adopted for odometry estimation. To realize more robust localization results, two Kalman filter loops are used with the robot kinematic model to fuse wheel encoder, IMU, LiDAR odometry, and a low-cost GNSS receiver data. Besides, a recognition network based on YOLO v3 is deployed to realize real-time recognition of cracks and people during surveillance. As a system, by connecting the robot, the cloud server and the users with IOT technology, the proposed solution could be more robust and practical.

show abstract

“…For land robots, dead reckoning is another reliable source of odometry. A robust AHRS could improve the wheel dead reckoning well [23].…”

Section: Related Workmentioning

confidence: 99%

Autonomous Dam Surveillance Robot System Based on Multi-Sensor Fusion

Zhang

Zhan

Wang

et al. 2020

Sensors

View full text Add to dashboard Cite

show abstract

“…When the vehicle enters the garage, navigation accuracy will be reduced due to the GPS signal attenuation. Hence, to avoid this situation occurring, a switching algorithm, which can turn the integrated navigation mode into the DR navigation mode, should be applied at the underground garage entrance [20,21]. Moreover, we need some constraints to judge whether the navigation algorithm should be switched at one epoch or not.…”

Section: Garage Entrance Switching Decisionmentioning

confidence: 99%

A Low Cost Civil Vehicular Seamless Navigation Technology Based on Enhanced RISS/GPS between the Outdoors and an Underground Garage

et al. 2020

View full text Add to dashboard Cite

Vehicles have to rely on satellite navigation in an open environment. However, satellite navigation cannot obtain accurate positioning information for vehicles in the interior of underground parking lots, as they comprise a semi-enclosed navigation space. Therefore, vehicular navigation needs to take into consideration both outdoor and indoor environments. Actually, outdoor navigation and indoor navigation require different positioning methods, and it is of great importance to choose a reasonable navigation and positioning algorithm solution for vehicles. Fortunately, the integrated navigation of the Global Positioning System (GPS) and the Micro-Electro-Mechanical System (MEMS) inertial navigation system could solve the problem of switching navigation algorithms in the entrance and exit of underground parking lots. This paper proposes a low cost vehicular seamless navigation technology based on the reduced inertial sensor system (RISS)/GPS between the outdoors and an underground garage. Specifically, the enhanced RISS is a positioning algorithm based on three inertial sensors and one odometer, which could achieve a similar location effect as the full model integrated navigation, reduce the costs greatly, and improve the efficiency of each sensor.

show abstract

“…The system is transferred to the inertial navigation plus vehicle navigation mode. Through the DR algorithm [12], the current position of the vehicle can be accurately derived without satellite positioning support. The vehicle navigation system determines whether the navigation runs outdoors based on the PDOP or not [13].…”

Section: Introductionmentioning

confidence: 99%

A Low-Cost Underground Garage Navigation Switching Algorithm Based on Kalman Filtering

Gao

Wang

Liu

et al. 2019

Sensors

View full text Add to dashboard Cite

Modern parking lots have gradually developed into underground garages to improve the efficient use of space. However, the complex design of parking lots also increases the demands on vehicle navigation. The traditional method of navigation switching only uses satellite signals. After the Position Dilution Of Precision (PDOP) of satellite signals is over the limit, vehicle navigation will enter indoor mode. It is not suitable for vehicles in underground garages to switch modes with a fast-response system. Therefore, this paper chooses satellite navigation, inertial navigation, and the car system to combine navigation. With the condition that the vehicle can freely travel through indoor and outdoor environments, high-precision outdoor environment navigation is used to provide the initial state of underground navigation. The position of the vehicle underground is calculated by the Dead Reckoning (DR) navigation system. This paper takes advantage of the Extended Kalman Filter (EKF) algorithm to provide two freely switchable navigation modes for vehicles in ground and underground garages. The continuity, robustness, fast response, and low cost of the indoor and outdoor switching navigation methods are verified in real-time systems.

show abstract

Experimental analysis of a low-cost dead reckoning navigation system for a land vehicle using a robust AHRS

Cited by 19 publications

References 29 publications

Autonomous Dam Surveillance Robot System Based on Multi-Sensor Fusion

Autonomous Dam Surveillance Robot System Based on Multi-Sensor Fusion

A Low Cost Civil Vehicular Seamless Navigation Technology Based on Enhanced RISS/GPS between the Outdoors and an Underground Garage

A Low-Cost Underground Garage Navigation Switching Algorithm Based on Kalman Filtering

Contact Info

Product

Resources

About