Search for Initial Conditions for Sustained Hopping of Passive Springy-Leg Offset-Mass Hopping Robot

2007 ◽  
Vol 129 (4) ◽  
pp. 522-526 ◽  
Author(s):  
B. Seth ◽  
P. Seshu ◽  
P. V. Shanmuganathan ◽  
V. V. Vichare ◽  
P. Raj
Keyword(s):  
Genetic Algorithm ◽  
Search Strategy ◽  
Initial Conditions ◽  
Center Of Gravity ◽  
The Body ◽  
Hopping Robot ◽  
Spring Force

A springy-leg, offset-mass or SLOM hopper configuration is considered here, wherein the center of gravity of the body is offset from the line of action of spring force. It is observed that this feature tends to extend the passive hopping motion. A heuristics-based search strategy and a genetic algorithm-based search strategy are implemented for finding the initial conditions that result in extended hopping motion.

Shifting of the body center of gravity in low-risk preterm infants: A video-pedoscope study

2018 ◽  
Vol 124 ◽  
pp. 33-37 ◽  
Author(s):  
Natascia Bertoncelli ◽  
Laura Lucaccioni ◽  
Luca Ori ◽  
Christa Einspieler ◽  
Heinz F.R. Prechtl ◽  
...  
Keyword(s):  
Preterm Infants ◽  
Center Of Gravity ◽  
The Body ◽  
Low Risk ◽  
Body Center

scholarly journals Scalable co-optimization of morphology and control in embodied machines

2018 ◽  
Vol 15 (143) ◽  
pp. 20170937 ◽  
Author(s):  
Nick Cheney ◽  
Josh Bongard ◽  
Vytas SunSpiral ◽  
Hod Lipson
Keyword(s):  
Embodied Cognition ◽  
Initial Conditions ◽  
Control Policy ◽  
Sensorimotor Control ◽  
Body Plan ◽  
The Body ◽  
Test Bed ◽  
Local Optima ◽  
Close Coupling ◽  
And Control

Evolution sculpts both the body plans and nervous systems of agents together over time. By contrast, in artificial intelligence and robotics, a robot's body plan is usually designed by hand, and control policies are then optimized for that fixed design. The task of simultaneously co-optimizing the morphology and controller of an embodied robot has remained a challenge. In psychology, the theory of embodied cognition posits that behaviour arises from a close coupling between body plan and sensorimotor control, which suggests why co-optimizing these two subsystems is so difficult: most evolutionary changes to morphology tend to adversely impact sensorimotor control, leading to an overall decrease in behavioural performance. Here, we further examine this hypothesis and demonstrate a technique for ‘morphological innovation protection’, which temporarily reduces selection pressure on recently morphologically changed individuals, thus enabling evolution some time to ‘readapt’ to the new morphology with subsequent control policy mutations. We show the potential for this method to avoid local optima and converge to similar highly fit morphologies across widely varying initial conditions, while sustaining fitness improvements further into optimization. While this technique is admittedly only the first of many steps that must be taken to achieve scalable optimization of embodied machines, we hope that theoretical insight into the cause of evolutionary stagnation in current methods will help to enable the automation of robot design and behavioural training—while simultaneously providing a test bed to investigate the theory of embodied cognition.

scholarly journals A MODIFIED GENETIC ALGORITHM FOR FINDING FUZZY SHORTEST PATHS IN UNCERTAIN NETWORKS

2016 ◽  
Vol XLI-B2 ◽  
pp. 299-304 ◽  
Author(s):  
A. A. Heidari ◽  
M. R. Delavar
Keyword(s):  
Genetic Algorithm ◽  
Shortest Path ◽  
Shortest Paths ◽  
The Body ◽  
Shortest Path Problems ◽  
Conventional Procedure ◽  
Path Lengths ◽  
The Cost ◽  
Uncertain Networks ◽  
Exploration Exploitation

In realistic network analysis, there are several uncertainties in the measurements and computation of the arcs and vertices. These uncertainties should also be considered in realizing the shortest path problem (SPP) due to the inherent fuzziness in the body of expert's knowledge. In this paper, we investigated the SPP under uncertainty to evaluate our modified genetic strategy. We improved the performance of genetic algorithm (GA) to investigate a class of shortest path problems on networks with vague arc weights. The solutions of the uncertain SPP with considering fuzzy path lengths are examined and compared in detail. As a robust metaheuristic, GA algorithm is modified and evaluated to tackle the fuzzy SPP (FSPP) with uncertain arcs. For this purpose, first, a dynamic operation is implemented to enrich the exploration/exploitation patterns of the conventional procedure and mitigate the premature convergence of GA technique. Then, the modified GA (MGA) strategy is used to resolve the FSPP. The attained results of the proposed strategy are compared to those of GA with regard to the cost, quality of paths and CPU times. Numerical instances are provided to demonstrate the success of the proposed MGA-FSPP strategy in comparison with GA. The simulations affirm that not only the proposed technique can outperform GA, but also the qualities of the paths are effectively improved. The results clarify that the competence of the proposed GA is preferred in view of quality quantities. The results also demonstrate that the proposed method can efficiently be utilized to handle FSPP in uncertain networks.

scholarly journals Generation of Suitable Jumping Motion Pattern for Hopping Robot under Genetic Algorithm

2000 ◽  
Vol 120 (10) ◽  
pp. 1365-1371
Author(s):  
Yoshida Yoshiro ◽  
Kamano Takyua ◽  
Yasuno Takashi ◽  
Suzuki Takayuki ◽  
Harada Hironobu ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Motion Pattern ◽  
Hopping Robot

scholarly journals Stabilisation and drag reduction of pipe flows by flattening the base profile

2019 ◽  
Vol 863 ◽  
pp. 850-875 ◽  
Author(s):  
Elena Marensi ◽  
Ashley P. Willis ◽  
Rich R. Kerswell
Keyword(s):  
Drag Reduction ◽  
Nonlinear Stability ◽  
Pipe Flow ◽  
Body Force ◽  
Initial Conditions ◽  
Reynolds Numbers ◽  
Streamwise Velocity ◽  
The Body ◽  
Random Disturbance ◽  
Good Proxy

Recent experimental observations (Kühnen et al., Nat. Phys., vol. 14, 2018b, pp. 386–390) have shown that flattening a turbulent streamwise velocity profile in pipe flow destabilises the turbulence so that the flow relaminarises. We show that a similar phenomenon exists for laminar pipe flow profiles in the sense that the nonlinear stability of the laminar state is enhanced as the profile becomes more flattened. The flattening of the laminar base profile is produced by an artificial localised body force designed to mimic an obstacle used in the experiments of Kühnen et al. (Flow Turbul. Combust., vol. 100, 2018a, pp. 919–943) and the nonlinear stability measured by the size of the energy of the initial perturbations needed to trigger transition. Significant drag reduction is also observed for the turbulent flow when triggered by sufficiently large disturbances. In order to make the nonlinear stability computations more efficient, we examine how indicative the minimal seed – the disturbance of smallest energy for transition – is in measuring transition thresholds. We first show that the minimal seed is relatively robust to base profile changes and spectral filtering. We then compare the (unforced) transition behaviour of the minimal seed with several forms of randomised initial conditions in the range of Reynolds numbers $Re=2400$–$10\,000$ and find that the energy of the minimal seed after the Orr and oblique phases of its evolution is close to that of a critical localised random disturbance. In this sense, the minimal seed at the end of the oblique phase can be regarded as a good proxy for typical disturbances (here taken to be the localised random ones) and is thus used as initial condition in the simulations with the body force. The enhanced nonlinear stability and drag reduction predicted in the present study are an encouraging first step in modelling the experiments of Kühnen et al. and should motivate future developments to fully exploit the benefits of this promising direction for flow control.

Numerical Computation of Differential-Algebraic Equations for the Approximation of Artificial Satellite Trajectories and Planetary Ephemerides

1999 ◽  
Vol 67 (3) ◽  
pp. 574-580 ◽  
Author(s):  
B. Fox ◽  
L. S. Jennings ◽  
A. Y. Zomaya
Keyword(s):  
Differential Equations ◽  
Virtual Work ◽  
Initial Conditions ◽  
Artificial Satellite ◽  
System Modeling ◽  
Differential Algebraic Equations ◽  
The Body ◽  
Time Interval ◽  
Differential Algebraic Equation ◽  
Generalized Coordinates

The principle of virtual work and Lagrange’s equations of motion are used to construct a system of differential equations for constrained spatial multibody system modeling. The differential equations are augmented with algebraic constraints representing the system being modeled. The resulting system is a high index differential-algebraic equation (DAE) which is cast as an ordinary differential equation (ODE) by differentiating the constraint equations twice. The initial conditions are the heliocentric rectangular equatorial generalized coordinates and their first time derivatives of the planets of the solar system and an artificial satellite. The ODE is computed using the integration subroutine LSODAR to generate the body generalized coordinates and time derivatives and hence produce the planetary ephemerides and satellite trajectories for a time interval. Computer simulation and graphical output indicate the satellite and planetary positions and the latter may be compared with those provided in the Astronomical Almanac. Constraint compliance is investigated to establish the accuracy of the computation. [S0021-8936(00)03403-6]

A PASSIVE STATE SIMULATION OF AN ANAL SPHINCTER USING SIMMECHANICS

2018 ◽  
Vol 18 (06) ◽  
pp. 1850059
Author(s):  
BLANCA N. RIOS ATAXCA ◽  
CARLOS D. GARCÍA BELTRÁN ◽  
JOSÉ M. RODRÍGUEZ LELIS ◽  
VÍCTOR H. OLIVARES PEREGRINO ◽  
FLORENCIO DE LA CONCHA BERMEJILLO ◽  
...  
Keyword(s):  
Initial Conditions ◽  
Radial Force ◽  
The Body ◽  
Passive State ◽  
Sphincter Muscle ◽  
Human Beings ◽  
Concentrated Mass ◽  
Mechanical Oscillations ◽  
Spring System ◽  
Mass Spring

Nowadays, different mechanical artificial sphincters can be found implanted in human beings, trying to overcome a deficiency in the performance of the natural one. However, they do not take into account the natural anal sphincter’s (AS) dimensions, and autonomous response; they also lack in basic contraction and relaxation properties. In this paper, by addressing the AS behavior, an AS model designed with Matlab/SimMechanics is shown. The model comprises bodies of concentrated mass interconnected by springs. The mass–spring system is arranged in concentric rings where every concentrated mass is interconnected by a spring. Each spring takes specific stiffness, which varies with length, in accordance to an experimental curve. The system described can be loaded or unloaded, describing then the muscle behavior. Each element that forms the model of rings is subject to displacements caused by forces of traction and compression, when a radial force is applied from the center towards the inner ring. The springs of the inner ring experience forces of traction, whereas the springs that connect the body of the inner ring with the outer ring perpendicularly are submitted to compression forces.The data used in the proposed model corresponded to dimensions of the humanAS: width, height, rigidity, stress, tension, basically obtaining an initial deformation behavior according to the sphincter in the passive state. The model remained stable with some mechanical oscillations due to the elastic elements; by modifying one of the parameters, the behavior became unstable and unmanageable. It was verified that it is a sensitive model when modifying the initial conditions that the concrete data requires in case of reproducing the sphincter muscle with particular dimensions.

Towards a Hybrid Solver: Integration of a Genetic Algorithm Within “DSIDES”

2002 ◽  
Author(s):  
Shuiwei Xie ◽  
Warren F. Smith
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Linear Programming ◽  
Decision Support ◽  
Hybrid Genetic Algorithm ◽  
Systems Design ◽  
Nonlinear Problems ◽  
The Body ◽  
Hybrid Solver ◽  
Decision Based Design

In contributing to the body of knowledge for decision-based design, the work reported in this paper has involved steps towards building a hybrid genetic algorithm to address systems design. Highlighted is a work in progress at the Australian Defence Force Academy (ADFA). A genetic algorithm (GA) is proposed to deal with discrete aspects of a design model (e.g., allocation of space to function) and a sequential linear programming (SLP) method for the continuous aspects (e.g., sizing). Our historical Decision Based Design (DBD) tool has been the code DSIDES (Decision Support In the Design of Engineering Systems). The original functionality of DSIDES was to solve linear and non-linear goal programming styled problems using linear programming (LP) and sequential (adaptive) linear programming (SLP/ALP). We seek to enhance DSIDES’s solver capability by the addition of genetic algorithms. We will also develop the appropriate tools to deal with the decomposition and synthesis implied. The foundational paradigm for DSIDES, which remains unchanged, is the Decision Support Problem Technique (DSPT). Through introducing genetic algorithms as solvers in DSIDES, the intention is to improve the likelihood of finding the global minimum (for the formulated model) as well as the ability of dealing more effectively with nonlinear problems which have discrete variables, undifferentiable objective functions or undifferentiable constraints. Using some numerical examples and a practical ship design case study, the proposed GA based method is demonstrated to be better in maintaining diversity of populations, preventing premature convergence, compared with other similar GAs. It also has similar effectiveness in finding the solutions as the original ALP DSIDES solver.

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