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

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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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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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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Socially compliant mobile robot navigation via inverse reinforcement learning

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INTERNATIONAL JOURNAL OF robotICS RESEARCH 2016年第11期35卷 1352-1370页

作者： Kretzschmar, Henrik Spies, Markus Sprunk, Christoph Burgard, Wolfram Univ Freiburg Dept Comp Sci Freiburg Germany

mobile robots are increasingly populating our human environments. To interact with humans in a socially compliant way, these robots need to understand and comply with mutually accepted rules. In this paper, we present a novel approach to model the cooperative navigation behavior of humans. We model their behavior in terms of a mixture distribution that captures both the discrete navigation decisions, such as going left or going right, as well as the natural variance of human trajectories. Our approach learns the model parameters of this distribution that match, in expectation, the observed behavior in terms of user-defined features. To compute the feature expectations over the resulting high-dimensional continuous distributions, we use Hamiltonian Markov chain Monte Carlo sampling. Furthermore, we rely on a Voronoi graph of the environment to efficiently explore the space of trajectories from the robot's current position to its target position. Using the proposed model, our method is able to imitate the behavior of pedestrians or, alternatively, to replicate a specific behavior that was taught by tele-operation in the target environment of the robot. We implemented our approach on a real mobile robot and demonstrated that it is able to successfully navigate in an office environment in the presence of humans. An extensive set of experiments suggests that our technique outperforms state-of-the-art methods to model the behavior of pedestrians, which also makes it applicable to fields such as behavioral science or computer graphics.

关键词： mobile robot dynamics REINFORCEMENT learning MONTE Carlo method TRAJECTORIES (Mechanics) MATHEMATICAL models

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Dynamic Detection of Topological Information from Grid-Based Generalized Voronoi Diagrams

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MATHEMATICAL PROBLEMS IN ENGINEERING 2013年第1期2013卷 1-11页

作者： Qin, Long Yin, Quanjun Zha, Yabing Peng, Yong Natl Univ Def Technol Coll Informat Syst & Management Changsha 410073 Hunan Peoples R China

In the context of robotics, the grid-based Generalized Voronoi Diagrams (GVDs) are widely used by mobile robots to represent their surrounding area. Current approaches for incrementally constructing GVDs mainly focus on providing metric skeletons of underlying grids, while the connectivity among GVD vertices and edges remains implicit, which makes high-level spatial reasoning tasks impractical. In this paper, we present an algorithm named Dynamic Topology Detector (DTD) for extracting a GVD with topological information from a grid map. Beyond the construction and reconstruction of a GVD on grids, DTD further extracts connectivity among the GVD edges and vertices. DTD also provides efficient repair mechanism to treat with local changes, making it work well in dynamic environments. Simulation tests in representative scenarios demonstrate that (1) compared with the static algorithms, DTD generally makes an order of magnitude improvement regarding computation times when working in dynamic environments;(2) with negligible extra computation, DTD detects topologies not computed by existing incremental algorithms. We also demonstrate the usefulness of the resulting topological information for high-level path planning tasks.

关键词： VORONOI polygons COMPUTATIONAL grids (Computer systems) TOPOLOGY ALGORITHMS SIMULATION methods & models DATA extraction PATH planning (robotics) mobile robot dynamics

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Practical Stabilization of Uncertain Nonholonomic mobile robots Based on Visual Servoing Model with Uncalibrated Camera Parameters

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MATHEMATICAL PROBLEMS IN ENGINEERING 2013年第1期2013卷 1-9页

作者： Chen, Hua Chen, Bingyan Li, Baojun Zhang, Jinbo Hohai Univ Dept Math & Phys Changzhou 213022 Jiangsu Peoples R China Hohai Univ Jiangsu Key Lab Power Transmiss & Distribut Equip Changzhou 213022 Jiangsu Peoples R China

The practical stabilization problem is addressed for a class of uncertain nonholonomic mobile robots with uncalibrated visual parameters. Based on the visual servoing kinematic model, a new switching controller is presented in the presence of parametric uncertainties associated with the camera system. In comparison with existing methods, the new design method is directly used to control the original system without any state or input transformation, which is effective to avoid singularity. Under the proposed control law, it is rigorously proved that all the states of closed-loop system can be stabilized to a prescribed arbitrarily small neighborhood of the zero equilibrium point. Furthermore, this switching control technique can be applied to solve the practical stabilization problem of a kind of mobile robots with uncertain parameters (and angle measurement disturbance) which appeared in some literatures such as Morin et al. (1998), Hespanha et al. (1999), Jiang (2000), and Hong et al. (2005). Finally, the simulation results show the effectiveness of the proposed controller design approach.

关键词： UNCERTAIN system stability NONHOLONOMIC dynamical systems mobile robot dynamics PARAMETER estimation CLOSED loop systems

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Pitch Moment Generation and Measurement in a robotic Hummingbird

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INTERNATIONAL JOURNAL OF MICRO AIR VEHICLES 2013年第4期5卷 299-309页

作者： Karasek, Matej Nan, Yanghai Romanescu, Iulian Preumont, Andre Univ Libre Brussels Ecole Polytech Act Struct Lab Brussels Belgium Gheorghe Asachi Tech Univ Iasi Machine Mfg & Ind Management Fac Machine Tools & Tools Dept Iasi Romania

Micro Air Vehicles (MAVs) with flapping wings try to mimic their biological counterparts, insects and hummingbirds, as they can combine high agility manoeuvres with precision hovering flight. Near-hovering flapping flight is naturally unstable and needs to be stabilized actively. We present a novel mechanism for pitch moment generation in a robotic hummingbird that uses wing twist modulation via flexible wing root bars. A custom build force balance, sensitive enough to measure the cycle averaged pitch moment as well as lift force, is also presented. The introduced prototype mechanism generates pitch moment of up to +/- 0.5 mNm. Finally we integrate a Shape Memory Alloy (SMA) wire to actuate the wing root bar ends. We present achievable displacement versus bandwidth as well as generated pitch moment.

关键词： BOEING A160T (Military helicopter) MICRO air vehicles DRONE aircraft mobile robot design & construction mobile robot dynamics DESIGN & construction

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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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