scholarly journals Comparative stable walking gait optimization for small-sized biped robot using meta-heuristic optimization algorithms

2018 ◽  
Vol 40 (4) ◽  
pp. 407-424
Author(s):  
Tran Thien Huan ◽  
Ho Pham Huy Anh
Keyword(s):  
Humanoid Robot ◽  
Differential Evolution Algorithm ◽  
Biped Robot ◽  
The Novel ◽  
Biped Robots ◽  
Walking Gait ◽  
Gait Parameters ◽  
Lift Height ◽  
Evolution Algorithm ◽  
Gait Optimization

This paper proposes a new way to optimize the biped walking gait design for biped robots that permits stable and robust stepping with pre-set foot lifting magnitude. The new meta-heuristic CFO-Central Force Optimization algorithm is initiatively applied to optimize the biped gait parameters as to ensure to keep biped robot walking robustly and steadily. The efficiency of the proposed method is compared with the GA-Genetic Algorithm, PSO-Particle Swarm Optimization and Modified Differential Evolution algorithm (MDE). The simulated and experimental results carried on the prototype small-sized humanoid robot demonstrate that the novel meta-heuristic CFO algorithm offers an efficient and stable walking gait for biped robots with respect to a pre-set of foot-lift height value.

Torso pitch motion effects on walking gait for biped robots

2021 ◽  
pp. 1-11
Author(s):  
Long Li ◽  
Zhongqu Xie ◽  
Xiang Luo ◽  
Juanjuan Li ◽  
Yufeng He
Keyword(s):  
Energy Consumption ◽  
Biped Robot ◽  
Gait Pattern ◽  
Optimization Criterion ◽  
Pattern Generation ◽  
Biped Robots ◽  
Unit Distance ◽  
Pitch Motion ◽  
Walking Gait ◽  
Gait Parameters

Gait pattern generation has an important influence on the walking quality of biped robots. In most gait pattern generation method, it is usually assumed that the torso remains vertial during walking. It is very intuitive and simple. However, is the gait pattern of keeping the torso vertical the most efficient? This paper presents a gait pattern in which the torso has pitch motion during walking. We define the cyclic gait of a seven-link biped robot with multiple gait parameters. The gait parameters are determined by optimization. The optimization criterion is choosen to minimize the energy consumption per unit distance of the biped robot. In order to compare the energy consumption of the proposed gait pattern with the one of torso vertical gait pattern, we generate two sets of optimal gait with various walking step lengths and walking periods. The results show that the proposed gait pattern is more energy-efficiency than the torso vertical gait pattern.

scholarly journals Effects of Torso Pitch Motion on Energy Efficiency of Biped Robot Walking

2021 ◽  
Vol 11 (5) ◽  
pp. 2342
Author(s):  
Long Li ◽  
Zhongqu Xie ◽  
Xiang Luo ◽  
Juanjuan Li
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Biped Robot ◽  
Gait Pattern ◽  
Pattern Generation ◽  
Biped Robots ◽  
Pitch Motion ◽  
Double Support ◽  
Gait Parameters ◽  
Support Phase

Gait pattern generation has an important influence on the walking quality of biped robots. In most gait pattern generation methods, it is usually assumed that the torso keeps vertical during walking. It is very intuitive and simple. However, it may not be the most efficient. In this paper, we propose a gait pattern with torso pitch motion (TPM) during walking. We also present a gait pattern with torso keeping vertical (TKV) to study the effects of TPM on energy efficiency of biped robots. We define the cyclic gait of a five-link biped robot with several gait parameters. The gait parameters are determined by optimization. The optimization criterion is chosen to minimize the energy consumption per unit distance of the biped robot. Under this criterion, the optimal gait performances of TPM and TKV are compared over different step lengths and different gait periods. It is observed that (1) TPM saves more than 12% energy on average compared with TKV, and the main factor of energy-saving in TPM is the reduction of energy consumption of the swing knee in the double support phase and (2) the overall trend of torso motion is leaning forward in double support phase and leaning backward in single support phase, and the amplitude of the torso pitch motion increases as gait period or step length increases.

scholarly journals Formulation and Solution of an Inverse Reliability Problem to Simulate the Dynamic Behavior of COVID-19 Pandemic

2021 ◽  
Vol 22 (1) ◽  
pp. 91-107
Author(s):  
F. S. Lobato ◽  
G. M. Platt ◽  
G. B. Libotte ◽  
A. J. Silva Neto
Keyword(s):  
Dynamic Behavior ◽  
Differential Evolution Algorithm ◽  
Iteration Process ◽  
Real Data ◽  
The Novel ◽  
Design Variables ◽  
Different Types ◽  
Evolution Algorithm ◽  
Novel Coronavirus ◽  
Optimization Loop

Different types of mathematical models have been used to predict the dynamic behavior of the novel coronavirus (COVID-19). Many of them involve the formulation and solution of inverse problems. This kind of problem is generally carried out by considering the model, the vector of design variables, and system parameters as deterministic values. In this contribution, a methodology based on a double loop iteration process and devoted to evaluate the influence of uncertainties on inverse problem is evaluated. The inner optimization loop is used to find the solution associated with the highest probability value, and the outer loop is the regular optimization loop used to determine the vector of design variables. For this task, we use an inverse reliability approach and Differential Evolution algorithm. For illustration purposes, the proposed methodology is applied to estimate the parameters of SIRD (Susceptible-Infectious-Recovery-Dead) model associated with dynamic behavior of COVID-19 pandemic considering real data from China's epidemic and uncertainties in the basic reproduction number (R0). The obtained results demonstrate, as expected, that the increase of reliability implies the increase of the objective function value.

Design of a Biped Robot With Torsion Springs at the Joints for Reduced Energy Consumption During Walk

2009 ◽  
Author(s):  
Santosh Pratap Singh ◽  
Ashish Dutta ◽  
Anupam Saxena
Keyword(s):  
Energy Consumption ◽  
Degrees Of Freedom ◽  
Equations Of Motion ◽  
Biped Robot ◽  
Single Step ◽  
Biped Robots ◽  
Gait Parameters ◽  
Reduction Of Energy Consumption ◽  
Torsion Springs ◽  
Spring Constants

Biped robots have multiple degrees of freedom for walking and hence they consume a lot of energy. In this paper it is proposed that adding torsion springs at the joints of an 8 DOF biped will lead to reduced energy consumption during walk. First the dynamic equations of motion of the biped robot are obtained incorporating the torsion springs at the joints. Using the dynamic model the total energy consumed during walk was evaluated for a single step. A Genetic Algorithm (GA) based algorithm was developed for finding the energy optimal trajectory during gait by comparing all the possible trajectories. It is first proved that addition of torsion springs at the joints lead to reduction of energy consumption as compared to a biped with no springs. All the gait parameters were then optimized to get the optimum values for the spring constants at each joint, reference angle of springs and length of each step. It is proved that using these optimal parameters the proposed biped robot consumes the least energy.

Optimal stable gait for nonlinear uncertain humanoid robot using central force optimization algorithm

2019 ◽  
Vol 36 (2) ◽  
pp. 599-621 ◽  
Author(s):  
Tran Thien Huan ◽  
Ho Pham Huy Anh
Keyword(s):  
Differential Evolution ◽  
Humanoid Robot ◽  
Differential Evolution Algorithm ◽  
Humanoid Robots ◽  
Central Force ◽  
Content Type ◽  
Force Optimization ◽  
Gait Parameters ◽  
Stable Gait ◽  
Central Force Optimization

Purpose The purpose of this paper is to design a novel optimized biped robot gait generator which plays an important role in helping the robot to move forward stably. Based on a mathematical point of view, the gait design problem is investigated as a constrained optimum problem. Then the task to be solved is closely related to the evolutionary calculation technique. Design/methodology/approach Based on this fact, this paper proposes a new way to optimize the biped gait design for humanoid robots that allows stable stepping with preset foot-lifting magnitude. The newly proposed central force optimization (CFO) algorithm is used to optimize the biped gait parameters to help a nonlinear uncertain humanoid robot walk robustly and steadily. The efficiency of the proposed method is compared with the genetic algorithm, particle swarm optimization and improved differential evolution algorithm (modified differential evolution). Findings The simulated and experimental results carried out on the small-sized nonlinear uncertain humanoid robot clearly demonstrate that the novel algorithm offers an efficient and stable gait for humanoid robots with respect to accurate preset foot-lifting magnitude. Originality/value This paper proposes a new algorithm based on four key gait parameters that enable dynamic equilibrium in stable walking for nonlinear uncertain humanoid robots of which gait parameters are initiatively optimized with CFO algorithm.

A novel online gait optimization approach for biped robots with point-feet

2019 ◽  
Vol 25 ◽  
pp. 81
Author(s):  
Majid Anjidani ◽  
M.R. Jahed Motlagh ◽  
M. Fathy ◽  
M. Nili Ahmadabadi
Keyword(s):  
Learning Algorithm ◽  
Biped Robot ◽  
Optimization Method ◽  
Optimization Approach ◽  
Loop Model ◽  
Modeling Error ◽  
Environment Change ◽  
Biped Robots ◽  
Walking Gait ◽  
New Situation

Designing a stable walking gait for biped robots with point-feet is stated as a constrained nonlinear optimization problem which is normally solved by an offline numerical optimization method. On the result of an unknown modeling error or environment change, the designed gait may be ineffective and an online gait improvement is impossible after the optimization. In this paper, we apply Generalized Path Integral Stochastic Optimal Control to closed-loop model of planar biped robots with point-feet which leads to an online Reinforcement Learning algorithm to design the walking gait. We study the ability of the proposed method to adapt the controller of RABBIT, which is a planar biped robot with point-feet, for stable walking. The simulation results show that the method, starting a dynamically unstable initial gait, quickly compensates the modeling error and reaches to a walking with exponential stability and desired features in a new situation which was impossible by the past methods.

scholarly journals Optimal nature-walking gait for humanoid robot using Jaya optimization algorithm

2019 ◽  
Vol 11 (11) ◽  
pp. 168781401988808 ◽  
Author(s):  
Tran Thien Huan ◽  
Ho Pham Huy Anh ◽  
Cao Van Kien
Keyword(s):  
Differential Evolution ◽  
Optimization Algorithm ◽  
Humanoid Robot ◽  
Biped Robot ◽  
Humanoid Robots ◽  
Walking Gait ◽  
Identification Approach ◽  
Stable Gait ◽  
Evolution Algorithms ◽  
Differential Evolution Algorithms

This article proposes a new method used to optimize the design process of nature-walking gait generator that permits biped robot to stably and naturally walk with preset foot-lift magnitude. The new Jaya optimization algorithm is innovatively applied to optimize the biped gait four key parameters initiatively applied to ensure the uncertain nonlinear humanoid robot walks robustly and steadily. The efficiency of the proposed Jaya-based identification approach is compared with the central force optimization and improved differential evolution (modified differential evolution) algorithms. The simulation and experimental results tested on the original small-sized biped robot HUBOT-4 convincingly demonstrate that the novel proposed algorithm offers an efficient and stable gait for humanoid robots with precise height of foot-lift value.

scholarly journals How does ankle push-off balance the walking speed and energy efficiency of planar biped robots?

2021 ◽  
Vol 13 (4) ◽  
pp. 168781402110119
Author(s):  
Qiaoli Ji ◽  
Zhihui Qian ◽  
Lei Ren ◽  
Luquan Ren
Keyword(s):  
Energy Efficiency ◽  
Gait Cycle ◽  
Walking Speed ◽  
Biped Robot ◽  
Step Length ◽  
Cost Of Transport ◽  
Biped Robots ◽  
Walking Gait ◽  
Motion Performance ◽  
Step Transition

Ankle push-off is defined as the phase in which muscle-tendon units about the ankle joint generate a burst of positive power during the step-to-step transition in human walking. The dynamic walking of a biped robot can be effectively realized through ankle push-off. However, how to use ankle push-off to balance the walking speed and energy efficiency of biped robots has not been studied deeply. In this study, the effects of the step length (the inter-leg angle is 40°, 50°, and 60°), torque and timing of ankle push-off on the walking speed and energy efficiency of biped robots were studied. The results show that when the step length is 50°, the push-off torque is 30 N· m and the corresponding push-off timing occurs at 43% of the gait cycle, the simulated robot obtains a highly economical walking gait. The corresponding maximum normalized walking speed is 0.40, and the minimum mechanical cost of transport is 2.25. To acquire a more economical walking gait of biped robots, the amount of ankle push-off and the push-off timing need to be coordinated. The purpose of this study is to provide a reference for the influence of ankle push-off on the motion performance of biped robots.

scholarly journals Color Image Quantization Algorithm Based on Self-Adaptive Differential Evolution

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Qinghua Su ◽  
Zhongbo Hu
Keyword(s):  
Differential Evolution ◽  
Color Image ◽  
Differential Evolution Algorithm ◽  
Optimization Methods ◽  
Particle Swarm Algorithm ◽  
The Novel ◽  
Image Quantization ◽  
Adaptive Differential Evolution ◽  
Evolution Algorithm ◽  
Self Adaptive

Differential evolution algorithm (DE) is one of the novel stochastic optimization methods. It has a better performance in the problem of the color image quantization, but it is difficult to set the parameters of DE for users. This paper proposes a color image quantization algorithm based on self-adaptive DE. In the proposed algorithm, a self-adaptive mechanic is used to automatically adjust the parameters of DE during the evolution, and a mixed mechanic of DE andK-means is applied to strengthen the local search. The numerical experimental results, on a set of commonly used test images, show that the proposed algorithm is a practicable quantization method and is more competitive thanK-means and particle swarm algorithm (PSO) for the color image quantization.

Solving Problems in Chaos Control though an Differential Evolution Algorithm with Region Zooming

2011 ◽  
Vol 110-116 ◽  
pp. 5048-5056 ◽  
Author(s):  
Fei Gao ◽  
Yi Bo Qi ◽  
Qiang Yin ◽  
Jia Qing Xiao
Keyword(s):  
Differential Evolution ◽  
Chaos Control ◽  
Uniform Design ◽  
Differential Evolution Algorithm ◽  
Initial Population ◽  
The Novel ◽  
Objective Functions ◽  
Unstable Periodic Orbits ◽  
Evolution Algorithm ◽  
Best Parameters

In this paper, a novel scheme is propose to solve the problems in chaos control via a nonnegative multi–modal nonlinear optimization, which finds the unstable periodic orbits and best parameters of chaos system such that the objective function is minimized. The novel scheme embeds with a differential evolution algorithm consisting of techniques in three aspects: uniform design to the initial population, deflection and stretching to the objective functions, and the region zooming self–adaptively, which result in a much more effective searching mechanism with fine equilibrium between exploitation and exploration. To exhibit the new scheme’s performance, the experiments done to Hénon, Chen and Lü system are given, and the simulations done show that the method has better adaptability, dependability and robustness.

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