scholarly journals Fast Attitude Estimation System for Unmanned Ground Vehicle Based on Vision/Inertial Fusion

Machines ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 241
Author(s):  
Zhenhui Fan ◽  
Pengxiang Yang ◽  
Chunbo Mei ◽  
Qiju Zhu ◽  
Xiao Luo
Keyword(s):  
Attitude Estimation ◽  
Inertial Fusion ◽  
Test Results ◽  
Ground Vehicles ◽  
Ground Vehicle ◽  
The Road ◽  
Continuous Vision ◽  
Estimation System ◽  
Core Idea ◽  
Long Endurance

The attitude estimation system based on vision/inertial fusion is of vital importance and great urgency for unmanned ground vehicles (UGVs) in GNSS-challenged/denied environments. This paper aims to develop a fast vision/inertial fusion system to estimate attitude; which can provide attitude estimation for UGVs during long endurance. The core idea in this paper is to integrate the attitude estimated by continuous vision with the inertial pre-integration results based on optimization. Considering that the time-consuming nature of the classical methods comes from the optimization and maintenance of 3D feature points in the back-end optimization thread, the continuous vision section calculates the attitude by image matching without reconstructing the environment. To tackle the cumulative error of the continuous vision and inertial pre-integration, the prior attitude information is introduced for correction, which is measured and labeled by an off-line fusion of multi-sensors. Experiments with the open-source datasets and in road environments have been carried out, and the results show that the average attitude errors are 1.11° and 1.96°, respectively. The road test results demonstrate that the processing time per frame is 24 ms, which shows that the proposed system improves the computational efficiency.

Hysteresis loss of ultra-large off-the-road tire rubber compounds based on operating conditions at mine sites

2021 ◽  
pp. 095440702110155
Author(s):  
Shaosen Ma ◽  
Guangping Huang ◽  
Khaled Obaia ◽  
Soon Won Moon ◽  
Wei Victor Liu
Keyword(s):  
Large Strain ◽  
Tensile Tests ◽  
Operating Conditions ◽  
Hysteresis Loss ◽  
Strain Rates ◽  
Test Results ◽  
Tire Rubber ◽  
The Road ◽  
Rubber Compounds ◽  
Mine Sites

The objective of this study is to investigate the hysteresis loss of ultra-large off-the-road (OTR) tire rubber compounds based on typical operating conditions at mine sites. Cyclic tensile tests were conducted on tread and sidewall compounds at six strain levels ranging from 10% to 100%, eight strain rates from 10% to 500% s−1 and 14 rubber temperatures from −30°C to 100°C. The test results showed that a large strain level (e.g. 100%) increased the hysteresis loss of tire rubber compounds considerably. Hysteresis loss of tire rubber compounds increased with a rise of strain rates, and the increasing rates became greater at large strain levels (e.g. 100%). Moreover, a rise of rubber temperatures caused a decrease in hysteresis loss; however, the decrease became less significant when the rubber temperatures were above 10°C. Compared with tread compounds, sidewall compounds showed greater hysteresis loss values and more rapid increases in hysteresis loss with the rising strain rate.

Improved AEB algorithm combined with estimating the adhesion coefficient of road ahead and considering the performance of EHB

2021 ◽  
pp. 095440702110261
Author(s):  
Dequan Zeng ◽  
Zhuoping Yu ◽  
Lu Xiong ◽  
Junqiao Zhao ◽  
Peizhi Zhang ◽  
...  
Keyword(s):  
Joint Probability ◽  
Principal Component ◽  
Test Results ◽  
Safe Distance ◽  
Adhesion Coefficient ◽  
The Road ◽  
Response Characteristics ◽  
Emergency Braking ◽  
Multiple Beams ◽  
Maximum Method

This paper proposes an improved autonomous emergency braking (AEB) algorithm intended for intelligent vehicle. Featuring a combination with the estimation of road adhesion coefficient, the proposed approach takes into account the performance of electronic hydraulic brake. In order for the accurate yet fast estimate of road ahead adhesion coefficient, the expectation maximization framework is applied depending on the reflectivity of ground extracted by multiple beams lidar in four major steps, which are the rough extraction of ground points based on 3 σ criterion, the accurate extraction of ground points through principal component analysis (PCA), the main distribution characteristics of ground as extracted using the expectation maximum method (EM) and the estimation of road adhesion coefficient via joint probability. In order to describe the performance of EHB, the response characteristics, as well as the forward and adverse models of both braking pressure and acceleration are obtained. Then, with two typical roads including single homogeneous road and fragment pavement, the safe distance of improved AEB is modeled. To validate the algorithm developed in this paper, various tests have been conducted. According to the test results, the reflectivity of laser point cloud is effective in estimating the road adhesion coefficient. Moreover, considering the performance of EHB system, the improved AEB algorithm is deemed more consistent with the practicalities.

A Perception-Based Fuzzy Route Planing Algorithm for Autonomous Unmanned Ground Vehicles

2018 ◽  
Vol 06 (04) ◽  
pp. 251-266
Author(s):  
Phillip J. Durst ◽  
Christopher T. Goodin ◽  
Cindy L. Bethel ◽  
Derek T. Anderson ◽  
Daniel W. Carruth ◽  
...  
Keyword(s):  
Path Planning ◽  
Urban Area ◽  
Route Planning ◽  
Unmanned Ground Vehicles ◽  
Membership Functions ◽  
Ground Vehicles ◽  
Ground Vehicle ◽  
Sensor Error ◽  
Planning Algorithm ◽  
Error Costs

Path planning plays an integral role in mission planning for ground vehicle operations in urban areas. Determining the optimum path through an urban area is a well-understood problem for traditional ground vehicles; however, in the case of autonomous unmanned ground vehicles (UGVs), additional factors must be considered. For an autonomous UGV, perception algorithms rather than platform mobility will be the limiting factor in operational capabilities. For this study, perception was incorporated into the path planning process by associating sensor error costs with traveling through nodes within an urban road network. Three common perception sensors were used for this study: GPS, LIDAR, and IMU. Multiple set aggregation operators were used to blend the sensor error costs into a single cost, and the effects of choice of aggregation operator on the chosen path were observed. To provide a robust path planning ability, a fuzzy route planning algorithm was developed using membership functions and fuzzy rules to allow for qualitative route planning in the case of generalized UGV performance. The fuzzy membership functions were then applied to several paths through the urban area to determine what sensors were optimized in each path to provide a measure of the UGV’s performance capabilities. The research presented in this paper shows the impacts that sensing/perception has on ground vehicle route planning by demonstrating a fuzzy route planning algorithm constructed by using a robust rule set that quantifies these impacts.

scholarly journals Proactive Guidance for Accurate UAV Landing on a Dynamic Platform: A Visual–Inertial Approach

Sensors ◽  
2022 ◽  
Vol 22 (1) ◽  
pp. 404
Author(s):  
Ching-Wei Chang ◽  
Li-Yu Lo ◽  
Hiu Ching Cheung ◽  
Yurong Feng ◽  
An-Shik Yang ◽  
...  
Keyword(s):  
Trajectory Optimization ◽  
Control Method ◽  
Guidance System ◽  
Autonomous Landing ◽  
Ground Vehicle ◽  
Ground Station ◽  
Moving Platforms ◽  
Promising Solution ◽  
Long Endurance ◽  
Indoor And Outdoor

This work aimed to develop an autonomous system for unmanned aerial vehicles (UAVs) to land on moving platforms such as an automobile or a marine vessel, providing a promising solution for a long-endurance flight operation, a large mission coverage range, and a convenient recharging ground station. Unlike most state-of-the-art UAV landing frameworks that rely on UAV onboard computers and sensors, the proposed system fully depends on the computation unit situated on the ground vehicle/marine vessel to serve as a landing guidance system. Such a novel configuration can therefore lighten the burden of the UAV, and the computation power of the ground vehicle/marine vessel can be enhanced. In particular, we exploit a sensor fusion-based algorithm for the guidance system to perform UAV localization, whilst a control method based upon trajectory optimization is integrated. Indoor and outdoor experiments are conducted, and the results show that precise autonomous landing on a 43 cm × 43 cm platform can be performed.

scholarly journals Two-Layer Routing for High-Voltage Powerline Inspection by Cooperated Ground Vehicle and Drone

2019 ◽  
Author(s):  
Yao Liu ◽  
Jianmai Shi ◽  
Zhong Liu ◽  
Jincai Huang ◽  
Tianren Zhou
Keyword(s):  
High Voltage ◽  
Road Network ◽  
Inspection System ◽  
Large Area ◽  
Technical Improvement ◽  
Routing Problem ◽  
Ground Vehicle ◽  
The Road ◽  
Battery Capacity ◽  
On The Road

A novel high-voltage powerline inspection system is investigated, which consists of the cooperated ground vehicle and drone. The ground vehicle acts as a mobile platform that can launch and recycle the drone, while the drone can fly over the powerline for inspection within limited endurance. This inspection system enables the drone to inspect powerline networks in a very large area. Both vehicle’ route in the road network and drone’s routes along the powerline network have to be optimized for improving the inspection efficiency, which generates a new two-layer point-arc routing problem. Two constructive heuristics are designed based on “Cluster First, Rank Second” and “Rank First, Split Second”. Then local search strategies are developed to further improve the quality of the solution. To test the performance of the proposed algorithms, practical cases with different-scale are designed based on the road network and powerline network of Ji’an, China. Sensitivity analysis on the parameters related with the drone’s inspection speed and battery capacity is conducted. Computational results indicate that technical improvement on the inspection sensor is more important for the cooperated ground vehicle and drone system.

Effect of Rear Wing on Time-Averaged Ground Vehicle Wake With Variable Slant Angle

2021 ◽  
Vol 143 (7) ◽  
Author(s):  
Md. Shehab Uddin ◽  
Fazlur Rashid
Keyword(s):  
Separation Bubble ◽  
Flow Property ◽  
Navier Stokes ◽  
Ground Vehicles ◽  
Slant Angle ◽  
Ground Vehicle ◽  
Rear Wing ◽  
Horseshoe Vortices ◽  
And Control ◽  
Ahmed Body

Abstract The slant angle plays a crucial role in the flow property of hatchback ground vehicles. An optimum slant angle is obligatory for better handling the ground vehicles when fitted with a rear wing. In this regard, the variation of time-averaged flow properties around a wing-attached hatchback ground vehicle (Ahmed body) due to a variable slant angle is accessed by this paper. The design includes a scaled Ahmed body as a reference ground vehicle and a rear wing with NACA 0018 profile. The computational studies are executed with Reynolds-averaged Navier–Stokes based k-epsilon turbulence model with nonequilibrium wall function. The vehicle's model is scaled to 75% of the actual model, and analyses are conducted with Reynolds number 2.7 × 106. After the study, it is observed that a 15 deg slant angle is the critical angle for the wing attached state in which the drag coefficient is maximum. After this angle, a sudden reduction of coefficients is observed, where 25 deg is critical for without wing condition. Besides this, the two counter-rotating horseshoe vortices in the separation bubble and side edge c-pillar vortices also behave differently due to the wing's presence. The turbulent kinetic energy variation and the variation in coefficients of surface pressure are also affected by the rear wing attachment. This paper will assist in finding the optimum slant angle for hatchback ground vehicles in the presence of a rear wing. Thus the study will help in increasing stability and control for hatchback ground vehicles.

A review on identification methods of road friction coefficient

2021 ◽  
Vol 15 ◽  
Author(s):  
Gengxin Qi ◽  
Xiaobin Fan ◽  
Hao Li
Keyword(s):  
Friction Coefficient ◽  
Autonomous Driving ◽  
Research Direction ◽  
Identification Methods ◽  
Research Status ◽  
The Road ◽  
Road Friction ◽  
Coefficient Measurement ◽  
Estimation System ◽  
Road Friction Coefficient

Background: The development of the tire/road friction coefficient measurement and estimation system has far-reaching significance for the active electronic control safety system of automobiles and is one of the core technologies for autonomous driving in the future. Objective: Estimating the road friction coefficient accurately and in real-time has become the leading research direction. Researchers have used different tools and proposed different algorithms and patents. These methods are widely used to estimate the road friction coefficient or other related parameters. This paper gives a comprehensive description of the research status in the field of road friction coefficient estimation. Method: According to the current research status of Chinese and foreign scholars in the field of road friction coefficient recognition, the recognition methods are mainly divided into two categories: Cause-based and Effect-based. Results: This literature review will discuss the existing two types of identification methods (Cause-based and Effect-based), and the applicable characteristics of each algorithm are analyzed. Conclusion: The two recognition methods are analyzed synthetically, and the development direction of road friction coefficient recognition technology is discussed.

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