Jumping behaviour for a wheeled quadruped robot: simulation and experiments

2013 ◽  
Vol 01 (01) ◽  
pp. 41-60 ◽  
Author(s):  
Adam Harmat ◽  
Michael Trentini ◽  
Inna Sharf
Keyword(s):  
Genetic Algorithm ◽  
High Speed ◽  
Degrees Of Freedom ◽  
Parameter Tuning ◽  
Quadruped Robot ◽  
Knee Joints ◽  
High Fidelity ◽  
Quadratic Response Surface ◽  
Quadratic Response ◽  
Hybrid Locomotion

In this paper, we describe a new jumping behaviour developed for the quadruped robot, PAW (Platform for Ambulating Wheels). The robot has very few degrees of freedom and no knee joints. It employs springy legs and wheels at the distal ends of the legs to achieve various modes of legged, wheeled, and hybrid locomotion, such as high-speed breaking, bounding, and presently jumping. The jumping maneuver developed in this manuscript is designed specifically to take advantage of the wheels on the robot and compliance in its legs and it involves the following principal stages: acceleration to jumping speed, body positioning via front hip thrusting, rear leg compression and thrusting, and flight. A high-fidelity MSC.ADAMS/Simulink co-simulation was developed and used to test and optimize the jumping process. Because of the strong coupling between the parameters defining the jump maneuver, manual parameter tuning is difficult and thus a genetic algorithm is employed for the optimization process. The data generated by the genetic algorithm is further used for the fitting of a quadratic response surface, which allows identifying those parameters that contribute most to a successful jump. Finally, the jumping maneuver is implemented on the physical PAW to demonstrate its feasibility on a hybrid quadruped, and to provide insights into the robot response during this highly dynamic maneuver.

scholarly journals Hybrid Seven-bar Press Mechanism

2018 ◽  
Vol 12 (3) ◽  
pp. 181-187
Author(s):  
M. Erkan Kütük ◽  
L. Canan Dülger
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Design Optimization ◽  
Hybrid System ◽  
Degrees Of Freedom ◽  
Dimensional Synthesis ◽  
Design Variables ◽  
Optimization Study ◽  
Metal Stamping

An optimization study with kinetostatic analysis is performed on hybrid seven-bar press mechanism. This study is based on previous studies performed on planar hybrid seven-bar linkage. Dimensional synthesis is performed, and optimum link lengths for the mechanism are found. Optimization study is performed by using genetic algorithm (GA). Genetic Algorithm Toolbox is used with Optimization Toolbox in MATLAB®. The design variables and the constraints are used during design optimization. The objective function is determined and eight precision points are used. A seven-bar linkage system with two degrees of freedom is chosen as an example. Metal stamping operation with a dwell is taken as the case study. Having completed optimization, the kinetostatic analysis is performed. All forces on the links and the crank torques are calculated on the hybrid system with the optimized link lengths

scholarly journals Aerodynamics of inclined cylindrical bodies free-flying in a hypersonic flowfield

2021 ◽  
Vol 62 (9) ◽  
Author(s):  
Patrick M. Seltner ◽  
Sebastian Willems ◽  
Ali Gülhan ◽  
Eric C. Stern ◽  
Joseph M. Brock ◽  
...  
Keyword(s):  
High Speed ◽  
Degrees Of Freedom ◽  
Numerical Data ◽  
Static Stability ◽  
Free Flight ◽  
Aerodynamic Coefficients ◽  
Flow Topology ◽  
Motion Data ◽  
Continuous Rotation ◽  
German Aerospace

Abstract The influence of the flight attitude on aerodynamic coefficients and static stability of cylindrical bodies in hypersonic flows is of interest in understanding the re/entry of space debris, meteoroid fragments, launch-vehicle stages and other rotating objects. Experiments were therefore carried out in the hypersonic wind tunnel H2K at the German Aerospace Center (DLR) in Cologne. A free-flight technique was employed in H2K, which enables a continuous rotation of the cylinder without any sting interferences in a broad angular range from 0$$^{\circ }$$ ∘ to 90$$^{\circ }$$ ∘ . A high-speed stereo-tracking technique measured the model motion during free-flight and high-speed schlieren provided documentation of the flow topology. Aerodynamic coefficients were determined in careful post-processing, based on the measured 6-degrees-of-freedom (6DoF) motion data. Numerical simulations by NASA’s flow solvers Cart3D and US3D were performed for comparison purposes. As a result, the experimental and numerical data show a good agreement. The inclination of the cylinder strongly effects both the flowfield and aerodynamic loads. Experiments and simulations with concave cylinders showed marked difference in aerodynamic behavior due to the presence of a shock–shock interaction (SSI) near the middle of the model. Graphic abstract

scholarly journals Getting High: High Fidelity Simulation of High Granularity Calorimeters with High Speed

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Erik Buhmann ◽  
Sascha Diefenbacher ◽  
Engin Eren ◽  
Frank Gaede ◽  
Gregor Kasieczka ◽  
...  
Keyword(s):  
Particle Physics ◽  
High Speed ◽  
Deep Neural Networks ◽  
High Fidelity ◽  
High Fidelity Simulation ◽  
Physical Processes ◽  
Electromagnetic Showers ◽  
Information Bottleneck ◽  
First Time ◽  
Processing Network

AbstractAccurate simulation of physical processes is crucial for the success of modern particle physics. However, simulating the development and interaction of particle showers with calorimeter detectors is a time consuming process and drives the computing needs of large experiments at the LHC and future colliders. Recently, generative machine learning models based on deep neural networks have shown promise in speeding up this task by several orders of magnitude. We investigate the use of a new architecture—the Bounded Information Bottleneck Autoencoder—for modelling electromagnetic showers in the central region of the Silicon-Tungsten calorimeter of the proposed International Large Detector. Combined with a novel second post-processing network, this approach achieves an accurate simulation of differential distributions including for the first time the shape of the minimum-ionizing-particle peak compared to a full Geant4 simulation for a high-granularity calorimeter with 27k simulated channels. The results are validated by comparing to established architectures. Our results further strengthen the case of using generative networks for fast simulation and demonstrate that physically relevant differential distributions can be described with high accuracy.

scholarly journals A new evaluation and prediction model of sound quality of high-speed permanent magnet motor based on genetic algorithm-radial basis function artificial neural network

2021 ◽  
Vol 104 (3) ◽  
pp. 003685042110311
Author(s):  
Kai Hu ◽  
Guangming Zhang ◽  
Wenyi Zhang
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Artificial Neural Network ◽  
Basis Function ◽  
High Speed ◽  
Objective Evaluation ◽  
Sound Quality ◽  
Average Error ◽  
Permanent Magnet Motor ◽  
Predicted Model

Sound quality (SQ) has become an important index to measure the competitiveness of motor products. To better evaluate and optimize SQ, a novelty SQ evaluation and prediction model of high-speed permanent magnet motor (HSPMM) with better accuracy is presented in this research. Six psychoacoustic parameters of A-weighted sound pressure level (ASPL), loudness, sharpness, roughness, fluctuation strength (FS), and perferred-frequency speech interference (PSIL) were adopted to objectively evaluate the SQ of HSPMM under multiple operating conditions and subjective evaluation was also conducted by the combination of semantic subdivision method and grade scoring method. The evaluation results show that the SQ is poor, which will have a certain impact on human psychology and physiology. The correlation between the objective evaluation parameters and the subjective scores is analyzed by coupling the subjective and objective evaluation results. The average error of multiple linear regression (MLR) model is 7.10%. It has good accuracy, but poor stability. In order to improve prediction accuracy, a new predicted model of radial basis function (RBF) artificial neural network was put forward based on genetic algorithm (GA) optimization. Compared with MLR, its average error rate is reduced by 3.16% and the standard deviation is reduced by 1.841. In addition, the weight of each objective parameter was analyzed. The new predicted model has a better accuracy. It can evaluate and optimize the SQ exactly. The research methods and conclusions of this paper can be extended to the evaluation, prediction, and optimization of SQ of other motors.

scholarly journals Optimization of Air Gap Length and Capacitive Auxiliary Winding in Three-Phase Induction Motors Based on a Genetic Algorithm

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4407
Author(s):  
Mbika Muteba
Keyword(s):  
Genetic Algorithm ◽  
Design Process ◽  
Power Factor ◽  
High Speed ◽  
High Efficiency ◽  
Air Gap ◽  
Element Analysis ◽  
Three Phase ◽  
High Torque ◽  
Cage Induction Motor

There is a necessity to design a three-phase squirrel cage induction motor (SCIM) for high-speed applications with a larger air gap length in order to limit the distortion of air gap flux density, the thermal expansion of stator and rotor teeth, centrifugal forces, and the magnetic pull. To that effect, a larger air gap length lowers the power factor, efficiency, and torque density of a three-phase SCIM. This should inform motor design engineers to take special care during the design process of a three-phase SCIM by selecting an air gap length that will provide optimal performance. This paper presents an approach that would assist with the selection of an optimal air gap length (OAL) and optimal capacitive auxiliary stator winding (OCASW) configuration for a high torque per ampere (TPA) three-phase SCIM. A genetic algorithm (GA) assisted by finite element analysis (FEA) is used in the design process to determine the OAL and OCASW required to obtain a high torque per ampere without compromising the merit of achieving an excellent power factor and high efficiency for a three-phase SCIM. The performance of the optimized three-phase SCIM is compared to unoptimized machines. The results obtained from FEA are validated through experimental measurements. Owing to the penalty functions related to the value of objective and constraint functions introduced in the genetic algorithm model, both the FEA and experimental results provide evidence that an enhanced torque per ampere three-phase SCIM can be realized for a large OAL and OCASW with high efficiency and an excellent power factor in different working conditions.

A Magnetic Drive Actuator for Micro Electrical Discharge Machining

2012 ◽  
Vol 591-593 ◽  
pp. 303-306
Author(s):  
Xiao You Zhang ◽  
Akio Kifuji ◽  
Dong Jue He
Keyword(s):  
Electrical Discharge ◽  
High Speed ◽  
Degrees Of Freedom ◽  
Electrical Discharge Machining ◽  
Magnetic Coupling ◽  
Magnetic Bearings ◽  
Coupling Mechanism ◽  
Micro Electrical Discharge Machining ◽  
Long Stroke ◽  
Magnetic Drive

Electrical discharge machining has the capability of machining all conductive materials regardless of hardness, and has the ability to deal with complex shapes. However, the speed and accuracy of conventional EDM are limited by probability and efficiency of the electrical discharges. This paper describes a three degrees of freedom (3-DOF) controlled, wide-bandwidth, high-precision, long-stroke magnetic drive actuator. The actuator can be attached to conventional electrical discharge machines to realize a high-speed and high-accuracy EDM. The actuator primarily consists of thrust and radial magnetic bearings, thrust and radial air bearings and a magnetic coupling mechanism. By using the thrust and radial magnetic bearings, the translational motions of the spindle can be controlled. The magnetic drive actuator possesses a positioning resolution of the order of micrometer, a bandwidth greater than 100Hz and a positioning stroke of 2mm.

Design, Construction and Control of a Remotely Operated Vehicle (ROV)

2011 ◽  
Author(s):  
Alireza Marzbanrad ◽  
Jalil Sharafi ◽  
Mohammad Eghtesad ◽  
Reza Kamali
Keyword(s):  
High Speed ◽  
Degrees Of Freedom ◽  
Remotely Operated Vehicle ◽  
Six Degrees Of Freedom ◽  
Depth Sensors ◽  
Control Schemes ◽  
On Line ◽  
Operation Unit ◽  
And Control ◽  
Design Construction

This is report of design, construction and control of “Ariana-I”, an Underwater Remotely Operated Vehicle (ROV), built in Shiraz University Robotic Lab. This ROV is equipped with roll, pitch, heading, and depth sensors which provide sufficient feedback signals to give the system six degrees-of-freedom actuation. Although its center of gravity and center of buoyancy are positioned in such a way that Ariana-I ROV is self-stabilized, but the combinations of sensors and speed controlled drivers provide more stability of the system without the operator involvement. Video vision is provided for the system with Ethernet link to the operation unit. Control commands and sensor feedbacks are transferred on RS485 bus; video signal, water leakage alarm, and battery charging wires are provided on the same multi-core cable. While simple PI controllers would improve the pitch and roll stability of the system, various control schemes can be applied for heading to track different paths. The net weight of ROV out of water is about 130kg with frame dimensions of 130×100×65cm. Ariana-I ROV is designed such that it is possible to be equipped with different tools such as mechanical arms, thanks to microprocessor based control system provided with two directional high speed communication cables for on line vision and operation unit.

A New Adaptive Higher Order Response Surface Method

2011 ◽  
Vol 243-249 ◽  
pp. 5946-5954 ◽  
Author(s):  
Feng Han ◽  
Zheng Liang Li ◽  
Wen Liang Fan
Keyword(s):  
Response Surface ◽  
Response Surface Method ◽  
Univariate Analysis ◽  
Higher Order ◽  
Ultimate State ◽  
Strongly Nonlinear ◽  
Surface Method ◽  
Quadratic Response Surface ◽  
Undetermined Coefficient ◽  
Quadratic Response

Response surface method has won numerous concerns in the reliability analysis of structure due to its simplicity and practicability, especially quadratic response surface taking no account of cross terms is most widely used. However, for the complex ultimate state curved surface corresponding to strongly nonlinear, the approximate accuracy of quadratic response surface is apparently not enough, causing a biggish error in estimation of reliability. Although, theoretically, higher order response surface method can resolve this problem, the sharp increase of undetermined coefficient reduces calculation efficiency, and even, cannot achieve. Therefore, on the basis of univariate analysis of multivariable function, an algorithm which can reasonably determine higher order response surface form is presented in this article, able to effectively reduce the number of undetermined coefficients in response surface, so as to reduce computational difficulties and put forward improving measures for possible problems; In addition, based on the tactics of number-theoretic setpoint, a type of scheme of number-theoretic selecting point applicable to response surface method has been developed. Finally, through the analysis of examples, the suggested algorithm was validated, with the result showing that the algorithm has good accuracy and efficiency.

Sign in / Sign up

Export Citation Format

Share Document