scholarly journals A Model-Based Method for Estimating the Attitude of Underground Articulated Vehicles

Sensors ◽  
2019 ◽  
Vol 19 (23) ◽  
pp. 5245 ◽  
Author(s):  
Lulu Gao ◽  
Fei Ma ◽  
Chun Jin
Keyword(s):  
Field Test ◽  
Degrees Of Freedom ◽  
Kinematic Model ◽  
Measurement Unit ◽  
Model Based ◽  
Proposed Model ◽  
Articulated Vehicles ◽  
Free Environment ◽  
And Control ◽  
Novel Model

This paper presents a novel model-based method for estimating the attitude of underground articulated vehicles (UAV). We selected the Load–Haul–Dump (LHD) vehicle as our application object, as it is a typical UAV. First, we established the involved models of the LHD vehicle, including a kinematic model, the linear and angular constraints of a center articulation model, and a dynamic four degrees-of-freedom (DOF) yaw model. Second, we designed a Kalman filter (KF) to integrate the kinematic and constraint models with the data from an inertial measurement unit (IMU), overcoming gyroscope drift and disturbances in external acceleration. In addition, we designed another KF to estimate the yaw based on the dynamic yaw model. The accuracy of the estimations was further enhanced by data fusion. Then, the proposed method was validated by a simulation and a field test under different dynamic conditions. The errors in the estimation of roll, pitch, and yaw were 3.8%, 2.4%, and 4.2%, respectively, in the field test. The estimated longitudinal acceleration was used to obtain the velocity of the LHD vehicle; the error was found to be 1.2%. A comparison of these results to those of other methods showed that the proposed method has high precision. The proposed model-based method will greatly benefit the location, navigation, and control of UAVs without any artificial infrastructure in a global positioning system (GPS)-free environment.

scholarly journals Control-Oriented Finger Kinematic Model: Geometry-Based Approach

2019 ◽  
Vol 11 (6) ◽  
Author(s):  
Jong-Seob Won ◽  
Nina Robson
Keyword(s):  
Degrees Of Freedom ◽  
Control Strategies ◽  
Kinematic Model ◽  
Systems Design ◽  
Single Parameter ◽  
Human Hand ◽  
Cylindrical Object ◽  
Proposed Model ◽  
Human Finger ◽  
And Control

Abstract This paper proposes a novel finger kinematic model for human hand configurations, which applies to the realization of a naturalistic human finger motion for robotic finger systems and artificial hands. The proposed finger model is derived based on the geometry of a hand shape grasping a virtual cylindrical object. The model is capable of describing the natural rotation configuration of the joints of a long finger with three degrees of freedom by a single parameter, i.e., the radius of a cylindrical object. Experimental validation of the model shows that it can simulate closely naturalistic human finger movements. With the use of the proposed model, discussions were made on how to achieve multifinger coordination that makes task-specific hand movements or a posture for specific hand actions. Due to the simplicity of the model to define joints angle configuration in a long finger by a single parameter, the combination of the proposed model and the multifinger coordination concept discussed can be seen as an inclusive framework in human-like hand systems design and control. This paper is the first step toward exploring future novel combined design–control strategies for the development of under-actuated prosthetic and powered orthotic devices for the naturalistic motion that are based on both Cartesian space trajectory tracking and joint angle coordination.

scholarly journals Model-Based Slippage Estimation to Enhance Planetary Rover Localization with Wheel Odometry

2021 ◽  
Vol 11 (12) ◽  
pp. 5490
Author(s):  
Anna Maria Gargiulo ◽  
Ivan di Stefano ◽  
Antonio Genova
Keyword(s):  
Inertial Measurement Unit ◽  
Correction Method ◽  
Harsh Environments ◽  
Measurement Unit ◽  
Planetary Rovers ◽  
Model Based ◽  
Accurate Knowledge ◽  
And Control ◽  
Wheeled Vehicles ◽  
Rover Localization

The exploration of planetary surfaces with unmanned wheeled vehicles will require sophisticated software for guidance, navigation and control. Future missions will be designed to study harsh environments that are characterized by rough terrains and extreme conditions. An accurate knowledge of the trajectory of planetary rovers is fundamental to accomplish the scientific goals of these missions. This paper presents a method to improve rover localization through the processing of wheel odometry (WO) and inertial measurement unit (IMU) data only. By accurately defining the dynamic model of both a rover’s wheels and the terrain, we provide a model-based estimate of the wheel slippage to correct the WO measurements. Numerical simulations are carried out to better understand the evolution of the rover’s trajectory across different terrain types and to determine the benefits of the proposed WO correction method.

scholarly journals Three-axis air-bearing based platform for small satellite attitude determination and control simulation

2005 ◽  
Vol 3 (03) ◽  
Author(s):  
J. Prado ◽  
G. Bisiacchi ◽  
L. Reyes ◽  
E. Vicente ◽  
F. Contreras ◽  
...  
Keyword(s):  
Attitude Control ◽  
Attitude Determination ◽  
Center Of Mass ◽  
Measurement Unit ◽  
Simulation Platform ◽  
Air Bearing ◽  
Small Satellites ◽  
Main Components ◽  
Free Environment ◽  
And Control

A frictionless environment simulation platform, utilized for accomplishing three-axis attitude control tests in small satellites, is introduced. It is employed to develop, improve, and carry out objective tests of sensors, actuators, and algorithms in the experimental framework. Different sensors (i.e. sun, earth, magnetometer, and an inertial measurement unit) are utilized to assess three-axis deviations. A set of three inertial wheels is used as primary actuators for attitude control, together with three mutually perpendicular magnetic coils intended for desaturation purposes, and as a backup control system. Accurate balancing, through the platform’s center of mass relocation into the geometrical center of the spherical air-bearing, significatively reduces gravitational torques, generating a virtually torque-free environment. A very practical balancing procedure was developed for equilibrating the table in the local horizontal plane, with a reduced final residual torque. A wireless monitoring system was developed for on-line and post-processing analysis; attitude data are displayed and stored, allowing properly evaluate the sensors, actuators, and algorithms. A specifically designed onboard computer and a set of microcontrollers are used to carry out attitude determination and control tasks in a distributed control scheme. The main components and subsystems of the simulation platform are described in detail.

scholarly journals Hybrid Model-Based Analysis of Underground Articulated Vehicles Steering Characteristics

2019 ◽  
Vol 9 (24) ◽  
pp. 5274
Author(s):  
Lulu Gao ◽  
Chun Jin ◽  
Yuchao Liu ◽  
Fei Ma ◽  
Zhipeng Feng
Keyword(s):  
Dynamic Model ◽  
Hybrid Model ◽  
Field Test ◽  
Steering System ◽  
Underground Mines ◽  
Maximum Deviation ◽  
Model Based ◽  
Articulated Vehicles ◽  
Steering Characteristics ◽  
Hydraulic Power Steering

Owing to the harsh environment of underground mines, autonomous underground articulated vehicles (UAVs) with precise control and positioning system are particularly important. However, the ambiguity of steering characteristics hinders the development of UAVs. This study presents a model-based method to uncover the steering characteristics of a UAV. Firstly, a hybrid model of UAV was established, which included a dynamic model of articulated frames and a model of the hydraulic power steering system. Secondly, a field test of a typical UAV, a load-haul-dump (LHD) with 4 m3 capacity, was carried out. In order to verify the correctness of the established model and the accuracy of the involved parameters, the field test results were used to verify the dynamic model in time and frequency domains. Then, the steering characteristics of the UAV were uncovered based on the verified hybrid model, and the results showed that the increased load would increase ‘oversteering’ under the same articulation angle and that the error of trajectory exceeded 0.3 m. In addition, the deviations of trajectories between the two frames were revealed during the transient steering process, and the maximum deviation reached 0.21 m when the velocity was 2 m/s and the articulation angle was 15°. The comprehensive results indicate that the steering characteristics of UAVs cannot be ignored in regard to precise autonomous control and positioning.

Development of a Hybrid Dynamic Model and Experimental Identification of Robotic Bulldozing

2012 ◽  
Vol 135 (2) ◽  
Author(s):  
Scott G. Olsen ◽  
Gary M. Bone
Keyword(s):  
Dynamic Model ◽  
Degrees Of Freedom ◽  
Control Strategies ◽  
Nonlinear Differential Equations ◽  
Model Framework ◽  
Modeling And Control ◽  
Low Level ◽  
Proposed Model ◽  
The Individual ◽  
And Control

The low-level modeling and control of mobile robots that interact forcibly with their environment, such as robotic excavation machinery, is a challenging problem that has not been adequately addressed in prior research. This paper investigates the low-level modeling of robotic bulldozing. The proposed model characterizes the three primary degrees-of-freedom (DOF) of the bulldozer, the blade position, the material accumulation on the blade, and the material distribution in the environment. It includes discrete operation modes contained within a hybrid dynamic model framework. The dynamics of the individual modes are represented by a set of linear and nonlinear differential equations. An instrumented scaled-down bulldozer and environment are developed to emulate the full scale operation. Model parameter estimation and validation are completed using experimental data from this system. The model is refined based on a global sensitivity analysis. The refined model is suitable for simulation and design of robotic bulldozing control strategies.

scholarly journals Masked Sentence Model Based on BERT for Move Recognition in Medical Scientific Abstracts

2019 ◽  
Vol 4 (4) ◽  
pp. 42-55
Author(s):  
Gaihong Yu ◽  
Zhixiong Zhang ◽  
Huan Liu ◽  
Liangping Ding
Keyword(s):  
Contextual Information ◽  
English Literature ◽  
Language Model ◽  
Classification Model ◽  
The Novel ◽  
Model Based ◽  
Contextual Features ◽  
Proposed Model ◽  
Novel Model ◽  
Fine Tune

Abstract Purpose Move recognition in scientific abstracts is an NLP task of classifying sentences of the abstracts into different types of language units. To improve the performance of move recognition in scientific abstracts, a novel model of move recognition is proposed that outperforms the BERT-based method. Design/methodology/approach Prevalent models based on BERT for sentence classification often classify sentences without considering the context of the sentences. In this paper, inspired by the BERT masked language model (MLM), we propose a novel model called the masked sentence model that integrates the content and contextual information of the sentences in move recognition. Experiments are conducted on the benchmark dataset PubMed 20K RCT in three steps. Then, we compare our model with HSLN-RNN, BERT-based and SciBERT using the same dataset. Findings Compared with the BERT-based and SciBERT models, the F1 score of our model outperforms them by 4.96% and 4.34%, respectively, which shows the feasibility and effectiveness of the novel model and the result of our model comes closest to the state-of-the-art results of HSLN-RNN at present. Research limitations The sequential features of move labels are not considered, which might be one of the reasons why HSLN-RNN has better performance. Our model is restricted to dealing with biomedical English literature because we use a dataset from PubMed, which is a typical biomedical database, to fine-tune our model. Practical implications The proposed model is better and simpler in identifying move structures in scientific abstracts and is worthy of text classification experiments for capturing contextual features of sentences. Originality/value T he study proposes a masked sentence model based on BERT that considers the contextual features of the sentences in abstracts in a new way. The performance of this classification model is significantly improved by rebuilding the input layer without changing the structure of neural networks.

Development of a Special Inertial Measurement Unit for UAV Applications

2012 ◽  
Vol 135 (1) ◽  
Author(s):  
Khaled S. Hatamleh ◽  
Ou Ma ◽  
Angel Flores-Abad ◽  
Pu Xie
Keyword(s):  
Degrees Of Freedom ◽  
Measurement Unit ◽  
Dynamics Modeling ◽  
Dynamics Model ◽  
Inertial Measurement ◽  
Six Degrees Of Freedom ◽  
On Line ◽  
Measurement Units ◽  
Sensor Models ◽  
And Control

Dynamics modeling is becoming more and more important in the development and control of unmanned aerial vehicles (UAV). An accurate model of a vehicle requires good knowledge of the dynamics properties and motion states, which are usually estimated with the help of integrated inertial measurement units (IMUs). This work develops a special six degrees of freedom IMU, which has the capability of measuring the angular accelerations. This paper introduces the design of the new IMU along with its sensor models and calibration procedures. The work introduces two experimental methods to verify the calibrated IMU readings. The IMU was designed to support an on-line methodology to estimate the parameters of UAV’s dynamics model that is currently being developed by the authors.

Neural network adaptive control of nonlinear systems preceded by hysteresis

2020 ◽  
Vol 32 (1) ◽  
pp. 104-112
Author(s):  
Xinlong Zhao ◽  
Qiang Su ◽  
Shengxin Chen ◽  
Yonghong Tan
Keyword(s):  
Neural Network ◽  
Adaptive Control ◽  
Controller Design ◽  
Experimental Tests ◽  
Adaptive Controller ◽  
Auxiliary Variable ◽  
Proposed Model ◽  
And Control ◽  
Novel Model ◽  
Hysteresis Characteristics

Neural network adaptive control is proposed for a class of nonlinear system preceded by hysteresis. A novel model is developed to represent the hysteresis characteristics in explicit form. Furthermore, the auxiliary variable of the proposed model is proved to be bounded, which is essential for controller design. Then, neural network adaptive controller is directly applied to mitigate the influence of the hysteresis without constructing the hysteresis inverse. The updated law and control law of the controllers are derived from Lyapunov stability theorem, so that the boundedness of the close-loop system is guaranteed. Finally, the experimental tests are carried out to validate the effectiveness of the proposed approach.

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