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Prediction and Experimental Validation of Power Consumption of Skid-Steer mobile robots in Manufacturing Environments

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JOURNAL OF INTELLIGENT & robotIC SYSTEMS 2019年第3-4期94卷 825-839页

作者： Canfield, Stephen L. Hill, Tristan W. Zuccaro, Stephen G. Tennessee Technol Univ Brown Hall 224115 West 10th St Cookeville TN 38505 USA

Skid-Steer mobile robots (SSMRs) provide a robust and simple mechanical drive platform making them useful in many applications. Power consumption is an important consideration in the design of any mobile robot and particularly important for SSMRs because of the slipping and corresponding friction that induce large loads on the drive system. The slipping behavior is generally characterized through Instantaneous Centers of Rotation (ICR) of the contact patches and it has been established that these are functions of the system dynamics. However, the existing SSMR power models generally treat these constraints at the kinematic level by assuming constant slip rates taken from empirical data. This paper demonstrates a method to evaluate SSMR power consumption based on slip parameters that are calculated as differential equations extracted from the equations of motion. The dynamic power model is validated and then implemented on two practical manufacturing applications in which a mobile robot is climbing on steel surfaces with primary power consumption due to turning and overcoming gravity. The applications show that the dynamic ICR model plays a significant role in estimating power requirements. The results further demonstrate that the power and energy requirements for a given task depend on the payload and motion along the task in a non-linear fashion, for example showing that the minimum payload does not necessarily correspond to the minimum energy use. This outcome suggests that dynamic effects can be used to find optimal trajectories to minimize power or energy requirements.

关键词： Skid-steer mobile robot Power consumption Energy consumption mobile robot dynamics Skid-steer position estimation Skid-steer slip prediction

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Machine Learning Aided Design and Analysis of a Novel Magnetically Coupled Ball Drive

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IEEE-ASME TRANSACTIONS ON MECHATRONICS 2019年第5期24卷 1942-1953页

作者： Gebre, Biruk A. Pochiraju, Kishore, V Stevens Inst Technol Dept Mech Engn Hoboken NJ 07030 USA

mobile robotic platforms navigating in unstructured and dynamic environments greatly benefit from unconstrained omnidirectional locomotion. Ground robots with spherical wheels (ball-driven robots) can enable agile omnidirectional mobility over a wide range of ground terrains. Slip occurrence at the drive and ground contact surfaces decreases actuation performance, especially during rapid vehicle acceleration and navigation on graded terrains. In this paper, the design of a new magnetically coupled ball drive that uses controllable magnetic forces to increase the transmittable actuation torque and improve traction performance is described. The design uses an internal support structure to magnetically couple the spherical wheel to the chassis enabling it to function as an omnidirectional axel. Using a model of the magnetically coupled ball drive, the slip/no-slip operational window of the new design is evaluated. A support vector classification machine is trained to classify the slip/no-slip regions and identify the relative importance scores of the feature parameters in order of their sensitivity. The classification provided insight into appropriate ranges of the critical parameters that can improve traction performance. Based on the classification of the design space, multiple design and operational points were obtained to guide the design process further. Magnetostatic simulations are then used to design space efficient magnetic arrays capable of generating coupling forces in the desired range. A prototype of the new ball drive design is developed, and the premise that the magnetically coupled ball drive can improve the slip performance is experimentally tested. The results show that it is possible to control the traction forces at both drive and ground surfaces using the magnetic coupling force and substantially increase the slip performance of the ball drive using the new design.

关键词： Wheels Magnetic levitation Force mobile robots Magnetostatics Magnetic noise Finite-element methods (FEM) machine learning magnetostatics mobile robot dynamics motion analysis parametric modeling spherical wheel support vector classifier

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Neural network-based adaptive tracking control of mobile robots in the presence of wheel slip and external disturbance force

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NEUROCOMPUTING 2016年 188卷 12-22页

作者： Hoang, Ngoc-Bach Kang, Hee-Jun Univ Ulsan Grad Sch Elect Engn Ulsan 680749 South Korea Univ Ulsan Sch Elect Engn Ulsan South Korea

In this paper, a novel adaptive tracking controller is proposed for mobile robots in presence of wheel slip and external disturbance force based on neural networks with online weight updating laws. The uncertainties due to the wheel slip and external force are compensated online by neural networks in order to achieve the desired tracking performance. The online weight updating laws are modified versions of the backpropagation with an e-modification term added for robustness. The global uniformly ultimately bounded stability of the system to an arbitrarily small neighborhood of the origin is proven using Lyapunov method. The validity of the proposed controller is confirmed by two simulation examples of tracking a straight line and a U-shape trajectory. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Neural network Adaptive control mobile robot dynamics Wheel slip Disturbance force

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Survey and comparative study of free simulation software for mobile robots

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robotICA 2016年第4期34卷 791-822页

作者： Torres-Torriti, M. Arredondo, T. Castillo-Pizarro, P. Pontificia Univ Catolica Chile Dept Elect Engn Alameda 340 Santiago Chile Univ Tecn Federico Santa Maria Dept Elect Valparaiso Chile

In robotics, simulation has become an essential tool for research, education, and design purposes. Various software tools for mobile robot simulation have been developed and have reached different levels of maturity in recent years. This paper presents a general survey of mobile robot simulation tools and discusses qualitative and quantitative aspects of selection of four major simulators publicly available at no cost: Carmen, Player-Stage-Gazebo, Open dynamics Engine, and Microsoft robotics Developer Studio. The comparison of the simulators is aimed at establishing the range of applications for which these are best suited as well as their accuracy for certain simulation tasks. The simulators chosen for detailed comparison were selected considering their level of maturity, modularity, and popularity among engineers and researchers. The qualitative comparison included a discussion of relevant features. The quantitative analysis entailed the development of a detailed dynamical model of a mobile robot on a road with varying slope. This model was used as benchmark to compare the accuracy of each simulator. The validity of the simulated results was also contrasted against measurements obtained from experiments with a real robot. This research and analysis should be very valuable to educators, engineers, and researchers who are always seeking adequate tools for simulating autonomous mobile robots.

关键词： mobile robots Simulation software Comparative survey mobile robot dynamics Physics engine

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Adaptive output-feedback control for trajectory tracking of electrically driven non-holonomic mobile robots

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IET CONTROL THEORY AND APPLICATIONS 2011年第6期5卷 830-838页

作者： Park, B. S. Yoo, S. J. Park, J. B. Choi, Y. H. Yonsei Univ Dept Elect & Elect Engn Seoul 120749 South Korea Chung Ang Univ Sch Elect & Elect Engn Seoul 156756 South Korea Kyonggi Univ Dept Elect Engn Suwon Kyonggi Do South Korea

In this study, the authors propose an adaptive output-feedback controller for trajectory tracking of electrically driven non-holonomic mobile robots in the presence of parametric uncertainties. A new adaptive observer using the transformation matrices is developed to estimate the unmeasured velocities of the mobile robot. By using the transformation matrices, the designed adaptive observer can deal with quadratic velocity terms caused by the Coriolis matrix in the mobile robot dynamics as well as uncertain parameters in quadratic velocity terms. Based on the designed adaptive observer, a simple tracking controller at the actuator level is induced from the dynamic surface design methodology. Using the Lyapunov stability theory, the authors prove that all errors in a closed-loop system are uniformly ultimately bounded and converge to an adjustable neighbourhood of the origin.

关键词： Spatial variables control adaptive control Lyapunov stability theory adaptive output feedback control stability Stability in control theory mobile robots adaptive observer closed loop systems robot dynamics matrix algebra mobile robot dynamics dynamic surface design methodology feedback Algebra Self-adjusting control systems Lyapunov methods Coriolis matrix uncertain systems closed loop system quadratic velocity trajectory tracking position control electrically driven nonholonomic mobile robot mobile robots observers parametric uncertainty transformation matrices

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Estimation of Terrain Forces and Parameters for Rigid-Wheeled Vehicles

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IEEE TRANSACTIONS ON robotICS 2009年第3期25卷 717-726页

作者： Ray, Laura E. Dartmouth Coll Thayer Sch Engn Hanover NH 03755 USA

This paper provides a methodology for the estimation of resistance, thrust, and resistive torques on each wheel of a rigid-wheeled vehicle generated at the vehicle-terrain interface, and from these forces and moments, a methodology to estimate terrain parameters is presented. Terrain force estimation, which is independent of a terrain model, can infer the ability to accelerate, climb, or tow a load independent of the underlying terrain properties. When a terrain model is available, parameters of that model, such as soil cohesion, friction angle, maximum normal stress, and stress distribution parameters, are determined from estimated vehicle-terrain forces using a multiple-model estimation approach, providing parameters that relate to accepted mobility metrics. The methodology requires a standard proprioceptive sensor suite-accelerometers, rate gyros, wheel speeds, motor torques, at A ground speed. Sinkage sensors are not required. Simulation results demonstrate efficacy of the method on three terrains spanning a range of soil cohesions reported in the literature.

关键词： mobile robot dynamics terrain factors

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Experimental Validation of an Underactuated Two-Wheeled mobile robot

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IEEE-ASME TRANSACTIONS ON MECHATRONICS 2009年第2期14卷 252-257页

作者： Oryschuk, Patrick Salerno, Alessio Al-Husseini, Abdul M. Angeles, Jorge Dassault Syst Inc Montreal PQ H2Y 1N9 Canada McGill Univ Dept Mech Engn Montreal PQ H3A 2K6 Canada McGill Univ Ctr Intelligent Machines Montreal PQ H3A 2K6 Canada Canadian Space Agcy Space Technol St Hubert PQ J3Y 8Y9 Canada

Reported in this paper are the implementation and testing of the real-time control of a two-wheeled mobile robot. The robot is underactuated, its mobility and control inputs being three and two, respectively. The control challenge faced here is to reduce the oscillations of the intermediate body while following a desired path. A controller, introduced elsewhere, is implemented using a real-time operating system on a novel control architecture. The control algorithm was tested using three different test motions: translational, rotational, and uphill.

关键词： Linear-quadratic control mobile robot dynamics mobile robot motion planning mobile robots motion control

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Evaluation of Terrain Parameter Estimation using a Stochastic Terrain Model

Evaluation of Terrain Parameter Estimation using a Stochasti...

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Conference on Unmanned Systems Technology XI

作者： Dumond, Danielle A. Ray, Laura E. Trautmann, Eric Dartmouth Coll Thayer Sch Engn Hanover NH 03755 USA

ISBN: (纸本)9780819475985

Autonomous vehicles driving on off-road terrain exhibit substantial variation in mobility characteristics even when the terrain is horizontal and qualitatively homogeneous. This paper presents a simple stochastic model for characterizing observed variability in vehicle response to terrain and for representing transitions between homogeneous terrain with local variability or between heterogeneous terrain types. Such a model provides a means for more realistic evaluation of terrain parameter estimation methods through simulation. A stochastic terrain model in which friction angle and soil cohesion are represented by Gaussian random variables qualitatively represents observed variability in traction vs. slip characteristics measured experimentally. The stochastic terrain model is used to evaluate a terrain parameter estimation method in which terrain forces are first estimated independent of a terrain model, and subsequently, parameters of a terrain model, such as soil cohesion, friction angle, and stress distribution parameters are determined from estimated vehicle-terrain forces. Simulation results show drawbar pull vs. slip characteristics resulting from terrain parameter estimation are within statistical bounds established by the stochastic terrain model.

关键词： mobile robot dynamics terrain factors

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Identification of coupled mathematical models for underwater vehicles

Identification of coupled mathematical models for underwater...

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Oceans 2007 Europe International Conference

作者： Miskovic, N. Vukic, Z. Barisic, M. Univ Zagreb Fac Elect & Comp Engn Dept Control & Comp Engn Lab UnderWater Syst & T Zagreb 41000 Croatia

ISBN: (纸本)9781424406340

The paper presents the procedure for identification of coupled mathematical models for underwater vehicles. The procedure is performed with the use of a simple laboratory apparatus that consists of a webcam placed above the experimental pool. The video recording of the underwater vehicle in motion is then analyzed in order to obtain relative speeds within the camera frame. The experiment uses a simple maneuver which excites the vehicle in all controllable directions (in the horizontal plane). The results have shown that even though the system under observation is nonholonomic, the sway motion occurs due to coupling. This allows for determination of dynamic model in uncontrollable directions. The experimental data also show which terms in a general dynamic model can be omitted when dealing with micro underwater vehicles, in order to preserve the simplicity.

关键词： identification underwater vehicles mobile robot dynamics

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A 6 DoF navigation algorithm for autonomous underwater vehicles

A 6 DoF navigation algorithm for autonomous underwater vehic...

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Oceans 2007 Europe International Conference

作者： Lammas, Andrew K. Sammut, Karl He, Fangpo Flinders Univ S Australia Sch Informat & Engn Intelligent Syst Res Grp Adelaide SA 5042 Australia

ISBN: (纸本)9781424406340

The objective of this paper is to compare the performance of a new proposed Measurement Assisted Partial Re-sampling (MAPR) filter against the performance of the Extended Kalman filter and the Mixture Monte Carlo Localizer within the context of a navigation algorithm for a dynamic 6 DoF system. In this paper, an autonomous underwater vehicle (AUV) is used as the dynamic system. The performances of the above three filters in resolving a navigation solution are assessed by giving the AUV a sequence of trajectories that highlight the sensitivities of the navigation algorithm to noise. This paper demonstrates that the MAPR filter is capable of computing an estimate that, like the EKF, takes into account the dynamics of the system, but like all particle filters is also capable of estimating non-Gaussian distributions.

关键词： Bayes procedures Kalman filtering mobile robot dynamics navigation recursive estimation particle filters

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