Motion Model of Two-Wheel Differential Drive Mobile Robot under Variable Load

2014 ◽  
Vol 668-669 ◽  
pp. 352-356 ◽  
Author(s):  
Zhi Hu Ruan ◽  
Niu Wang ◽  
Bing Xin Ran
Keyword(s):  
Mobile Robot ◽  
State Space Model ◽  
Response Characteristic ◽  
Model Parameters ◽  
Variable Load ◽  
Motion Model ◽  
Actual System ◽  
Wheel Load ◽  
Differential Drive ◽  
Entire Vehicle

Based on kinematics characteristic of two-wheeled differential drive mobile robot (WMR) and response characteristic of fact motor drive system, this paper presents the analysis method of the equivalent rotation inertia, and the entire vehicle load is assigned to each wheel, and then the wheel load is converted into the corresponding equivalent rotation inertia of the motor shaft of each wheel, and motion model of WMR are obtained for combining with quasi-equivalent (QE) state space model of double-loop direct current motor systems under variable load and kinematics model of WMR under the load changes. By using speed response data of the actual system and combining with genetic algorithm to accurately identify the model parameters. Finally, through experiments results of the WMR motion model and the second order model respectively comparing with the actual system which demonstrates the effectiveness of the proposing method and model.

scholarly journals Simulation of non-stationary stochastic ground motions based on recent Italian earthquakes

2021 ◽  
Author(s):  
Fabio Sabetta ◽  
Antonio Pugliese ◽  
Gabriele Fiorentino ◽  
Giovanni Lanzano ◽  
Lucia Luzi
Keyword(s):  
Ground Motion ◽  
Ground Motions ◽  
Strong Motion ◽  
Stochastic Simulations ◽  
Model Parameters ◽  
Motion Model ◽  
Arias Intensity ◽  
Time Frequency ◽  
Ground Motion Model ◽  
Ground Motion Records

AbstractThis work presents an up-to-date model for the simulation of non-stationary ground motions, including several novelties compared to the original study of Sabetta and Pugliese (Bull Seism Soc Am 86:337–352, 1996). The selection of the input motion in the framework of earthquake engineering has become progressively more important with the growing use of nonlinear dynamic analyses. Regardless of the increasing availability of large strong motion databases, ground motion records are not always available for a given earthquake scenario and site condition, requiring the adoption of simulated time series. Among the different techniques for the generation of ground motion records, we focused on the methods based on stochastic simulations, considering the time- frequency decomposition of the seismic ground motion. We updated the non-stationary stochastic model initially developed in Sabetta and Pugliese (Bull Seism Soc Am 86:337–352, 1996) and later modified by Pousse et al. (Bull Seism Soc Am 96:2103–2117, 2006) and Laurendeau et al. (Nonstationary stochastic simulation of strong ground-motion time histories: application to the Japanese database. 15 WCEE Lisbon, 2012). The model is based on the S-transform that implicitly considers both the amplitude and frequency modulation. The four model parameters required for the simulation are: Arias intensity, significant duration, central frequency, and frequency bandwidth. They were obtained from an empirical ground motion model calibrated using the accelerometric records included in the updated Italian strong-motion database ITACA. The simulated accelerograms show a good match with the ground motion model prediction of several amplitude and frequency measures, such as Arias intensity, peak acceleration, peak velocity, Fourier spectra, and response spectra.

Mechatronic Design of a Mobile Robot for Personal Assistance

2021 ◽  
Author(s):  
Luigi Tagliavini ◽  
Andrea Botta ◽  
Luca Carbonari ◽  
Giuseppe Quaglia ◽  
Dario Gandini ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Home Environment ◽  
State Of The Art ◽  
Assistive Robotics ◽  
Personal Assistance ◽  
Differential Drive ◽  
Electrical Systems ◽  
Moving Obstacles ◽  
Design Paradigm ◽  
Axisymmetric Shape

Abstract In this paper, a novel mobile platform for assistive robotics tasks is presented. The machine is designed for working in a home environment, un-structured and possibly occupied by people. To work in this space, the platform must be able to get rid of all the consequent difficulties: to overpass small objects as steps and carpets, to operate with an as-high-as-possible dynamics, to avoid moving obstacles, and to navigate autonomously to track persons for person monitoring purposes. The proposed platform is designed to have an omni-directional mobility that improves the manoeuvrability with respect to state-of-the-art differential drive robots. It also will have a non-axisymmetric shape to easily navigate narrow spaces, and real-time edge computing algorithms for navigation. This work shows the design paradigm adopted for the realization of a novel mobile robot, named Paquitop. For a robust output, the design process used a modular approach which disjointed the several sub-systems which compose the machine. After a brief analysis of the expected features, a set of basic requirements are drawn to guide the functional and executive design. The overall architecture of the platform is presented, together with some details on the mechanical and electrical systems.

scholarly journals Bayesian Analysis of Interleaved Learning and Response Bias in Behavioral Experiments

2007 ◽  
Vol 97 (3) ◽  
pp. 2516-2524 ◽  
Author(s):  
Anne C. Smith ◽  
Sylvia Wirth ◽  
Wendy A. Suzuki ◽  
Emery N. Brown
Keyword(s):  
Bayesian Analysis ◽  
State Space ◽  
State Space Model ◽  
Estimation Procedure ◽  
Ideal Observer ◽  
Model Parameters ◽  
Behavioral Experiments ◽  
Actual Object ◽  
Space Model ◽  
Multiple Tasks

Accurate characterizations of behavior during learning experiments are essential for understanding the neural bases of learning. Whereas learning experiments often give subjects multiple tasks to learn simultaneously, most analyze subject performance separately on each individual task. This analysis strategy ignores the true interleaved presentation order of the tasks and cannot distinguish learning behavior from response preferences that may represent a subject's biases or strategies. We present a Bayesian analysis of a state-space model for characterizing simultaneous learning of multiple tasks and for assessing behavioral biases in learning experiments with interleaved task presentations. Under the Bayesian analysis the posterior probability densities of the model parameters and the learning state are computed using Monte Carlo Markov Chain methods. Measures of learning, including the learning curve, the ideal observer curve, and the learning trial translate directly from our previous likelihood-based state-space model analyses. We compare the Bayesian and current likelihood–based approaches in the analysis of a simulated conditioned T-maze task and of an actual object–place association task. Modeling the interleaved learning feature of the experiments along with the animal's response sequences allows us to disambiguate actual learning from response biases. The implementation of the Bayesian analysis using the WinBUGS software provides an efficient way to test different models without developing a new algorithm for each model. The new state-space model and the Bayesian estimation procedure suggest an improved, computationally efficient approach for accurately characterizing learning in behavioral experiments.

scholarly journals Adaptive Model Predictive Vibration Control of a Cantilever Beam with Real-Time Parameter Estimation

2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
Gergely Takács ◽  
Tomáš Polóni ◽  
Boris Rohal’-Ilkiv
Keyword(s):  
Control System ◽  
Vibration Control ◽  
State Space ◽  
Real Time ◽  
Cantilever Beam ◽  
State Space Model ◽  
Model Parameters ◽  
Extended Kalman Filtering ◽  
Space Model ◽  
Continuous State

This paper presents an adaptive-predictive vibration control system using extended Kalman filtering for the joint estimation of system states and model parameters. A fixed-free cantilever beam equipped with piezoceramic actuators serves as a test platform to validate the proposed control strategy. Deflection readings taken at the end of the beam have been used to reconstruct the position and velocity information for a second-order state-space model. In addition to the states, the dynamic system has been augmented by the unknown model parameters: stiffness, damping constant, and a voltage/force conversion constant, characterizing the actuating effect of the piezoceramic transducers. The states and parameters of this augmented system have been estimated in real time, using the hybrid extended Kalman filter. The estimated model parameters have been applied to define the continuous state-space model of the vibrating system, which in turn is discretized for the predictive controller. The model predictive control algorithm generates state predictions and dual-mode quadratic cost prediction matrices based on the updated discrete state-space models. The resulting cost function is then minimized using quadratic programming to find the sequence of optimal but constrained control inputs. The proposed active vibration control system is implemented and evaluated experimentally to investigate the viability of the control method.

scholarly journals Battery state of charge estimation and online wheel slip ratio control for autonomous wheeled mobile robot

2021 ◽  
Author(s):  
Maral Partovibakhsh
Keyword(s):  
Kalman Filter ◽  
Power Consumption ◽  
Mobile Robot ◽  
Unscented Kalman Filter ◽  
Longitudinal Velocity ◽  
Accurate Estimation ◽  
Model Parameters ◽  
Slip Ratio ◽  
Soc Estimation ◽  
Increasing Function

For autonomous mobile robots moving in unknown environment, accurate estimation of available power along with the robot power demand for each mission is paramount to successful completion of that mission. Regarding the power consumption, the control unit deals with two tasks simultaneously: 1) it has to monitor the power supply (batteries) state of charge (SoC) constantly. This leads to estimation of robot current available power. Besides, batteries are sensitive to deep discharge or overcharge. The battery SoC is an essential factor in power management of a mobile robot. Accurate estimation of the battery SoC can improve power management, optimize the performance, extend the lifetime, and prevent permanent damage to the batteries. 2) The dynamic characteristics of the terrain the robot traverse requires rapid online modifications in its behaviour. The power required for driving a wheel is an increasing function of its slip ratio. For a wheeled robot moving for driving a wheel is an increasing function of its slip ratio. For a wheeled robot moving on different terrains, slip of the wheels should be checked and compensated for to keep the robot moving with less power consumption. To reduce the power consumption, the target robot moving with less power consumption. To reduce the power consumption, the target of the control system is to keep the slip ratio of the driving wheels around the desired value of the control system is to keep the slip ratio of the driving wheels around the desired value. To fulfill the above mentioned tasks, in this thesis, to increase model validity of lithium-ion battery in various charge/discharge scenarios during the mobile robot operation, the battery capacity fade and internal resistance change are modeled by adding them as state variables to a state space model. Using the output measured data, adaptive unscented Kalman Filter (AUKF) is employed for online model parameters identification of the equivalent circuit model at each sampling time. Subsequently, based on the updated model parameters, SoC estimation is conducted using AUKF. The effectiveness of the proposed method is verified through experiments under different power duties in the lab environment through experiments under different power duties in the lab environment. Better results are obtained both in battery model parameters estimation and the battery SoC estimation in comparison with other Kalman filter extensions. Furthermore, for effective control of the slip ratio, a model-based approach to estimating the longitudinal velocity of the mobile robot is presented. The AUKF is developed to estimate the vehicle longitudinal velocity and the wheel angular velocity using measurements from wheel encoders. Based on the estimated slip ratio, a sliding mode controller is designed for slip control of the uncertain nonlinear dynamical system in the presence of model uncertainties, parameter variations, and disturbances. Experiments are carried out in real time on a four-wheel mobile robot to verify the effectiveness of the estimation algorithm and the controller. It is shown that the controller is able to control the slip ratio of the mobile robot on different terrains while adaptive concept of AUKF leads to better results than the unscented Kalman filter in estimating the vehicle velocity which is difficult to measure in actual practice.

Simulation of a Differential-Drive Wheeled Mobile Lego Robot Mindstorms NXT

2015 ◽  
Vol 776 ◽  
pp. 319-324
Author(s):  
I. Wayan Widhiada ◽  
C.G. Indra Partha ◽  
Yuda A.P. Wayan Reza
Keyword(s):  
Mobile Robot ◽  
3D Model ◽  
Hardware Implementation ◽  
Movement Control ◽  
Common Environment ◽  
Matlab Simulink ◽  
Differential Drive ◽  
Simulation Results ◽  
Mechanical Elements ◽  
Drive Model

The aim of this paper is to model and simulate kinematics motion using the differential drive model of a mobile Lego robot Mindstorm NXT. The author’s use integrated two software as a method to solve the simulation of mobile lego robot mindstorms NXT using Matlab/Simulink and Solidworks software. These softwares are enable easier 3D model creation for both simulation and hardware implementation. A fundamental of this work is the use of Matlab/Simulink Toolboxes to support the simulation and understanding of the various kinematics systems and in particular how the SimMechanics toolbox is used to interface seamlessly with ordinary Simulink block diagrams to enable the mechanical elements and its associated control system elements to be investigated in one common environment. The result of simulation shows the mobile robot movement control based on decentralized point algorithm to follow the precision x and y references that has been specified. The design of the mobile robot is validated in simulation results as proof that this design can achieve the good performance.

A search for constraints on lithospheric net rotation in 2D convection simulations

2021 ◽  
Author(s):  
Suzanne Atkins ◽  
Nicolas Coltice
Keyword(s):  
Reference Frames ◽  
Plate Motion ◽  
Model Parameters ◽  
Motion Model ◽  
Motion Models ◽  
The Third ◽  
The Earth ◽  
Geological Past ◽  
Wide Range ◽  
Third Dimension

<p>Net rotation is the process whereby the entire lithosphere can rotate with respect to the Earth’s mantle. The plates and continents retain their location with respect to each other, but they change their position with respect to global reference frames such as the Earth’s magnetic dipole, and structures in the Earth’s mantle such as plumes and hotspots. Constraining lithospheric net rotation is therefore one factor in building an absolute plate motion model. However, the amount of net rotation occurring at present day is poorly contained, and the drivers of net rotation are very poorly understood. Many absolute plate motion models therefore attempt to minimise net rotation, because there is no way to constrain rotation in the geological past. </p><p> </p><p>In previous geodynamical studies, the presence of thick continents and large viscosity contrasts were found to be controlling factors in the development of net rotation. We investigate the effects of different convection parameters and tectonic states on the magnitude and evolution of net rotation in 2D simulations. The use of 2D simulations allows us to run enough simulations to study a wide range of model parameters. We intend to compare our 2D conclusions with 3D simulations, to investigate how much of a difference the third dimension makes.</p><p> </p><p>We find that net rotation varies on much shorter timescales than any other geodynamic feature. Net rotation is not cleanly correlated with any tectonic behaviours or settings, and that the magnitude and duration is unpredictable. We do however find that the distribution of net rotation within the lifetime of a particular simulation is Gaussian, with standard deviation dependent on the viscosity structure and contrasts of the simulation, in agreement with previous studies. However, in contrast to previous studies, the presence and thickness of continents makes very little difference to the speed of lithospheric rotation, although this may be because we are working in 2D. If the 2D results are also relevant in 3D, net rotation is a continuously varying and unpredictable value, but with a predictable statistical range. This may provide a way to better constrain net rotation for plate motion models.</p>

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