Biped Walking Using Coronal and Sagittal Movements Based on Truncated Fourier Series

Shafii, Nima; Reis, Luís Paulo; Lau, Nuno

doi:10.1007/978-3-642-20217-9_28

Cited by 22 publications

(24 citation statements)

References 22 publications

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“…After around 12000 iterations of optimization, GA improved the robot walking speed and reached a maximum stable velocity of 80.5 cm/s which is 54% faster than the best hand-tuned solution. Our optimized walking is faster than the agents in [1], [7], [13] and [15]. The average fitness value of different parameters setting is depicted in figure 9.…”

Section: Maximum Walking Speedmentioning

confidence: 99%

A Fast and Stable Omnidirectional Walking Engine for the Nao Humanoid Robot

Kasaei¹,

Lau²,

Pereira³

2019

Lecture Notes in Computer Science

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This paper proposes a framework designed to generate a closed-loop walking engine for a humanoid robot. In particular, the core of this framework is an abstract dynamics model which is composed of two masses that represent the lower and the upper body of a humanoid robot. Moreover, according to the proposed dynamics model, the low-level controller is formulated as a Linear-Quadratic-Gaussian (LQG) controller that is able to robustly track the desired trajectories. Besides, this framework is fully parametric which allows using an optimization algorithm to find the optimum parameters. To examine the performance of the proposed framework, a set of simulation using a simulated Nao robot in the RoboCup 3D simulation environment has been carried out. Simulation results show that the proposed framework is capable of providing fast and reliable omnidirectional walking. After optimizing the parameters using genetic algorithm (GA), the maximum forward walking velocity that we have achieved was 80.5cm/s.

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Section: Maximum Walking Speedmentioning

confidence: 99%

A Fast and Stable Omnidirectional Walking Engine for the Nao Humanoid Robot

Kasaei¹,

Lau²,

Pereira³

2019

Lecture Notes in Computer Science

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“…Recently, lots of studies focused in the improvement the efficiency of the biped gait generation problem. Shaffi in [6] introduced the robust humanoid walking using truncated Fourier series gait generator. New methods using intelligent algorithms applied for biped gait generation development, such as bee colony optimization algorithm [7], TS fuzzy controller [8], evolutionary computing [9].…”

Section: Introductionmentioning

confidence: 99%

Novel Stable Walking for Humanoid Robot Using Particle Swarm Optimization Algorithm

Huan¹,

Ánh²

2015

Advances in Intelligent Systems Research

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Abstract-This paper describes a novel walking gait generation algorithm based on inverse kinematics for a biped robot. The proposed algorithm uses the PSO (Particle Swarm Optimization) algorithm in order to find optimized values for the five walking algorithm parameters. The proposed experiment approach is tested on a small-sized humanoid robot in the DCSELAB, VNU-HCM. Simulation and experimental results reveal that using the PSO algorithm with an efficient fitness function can significantly reduce learning time. Moreover, a considerable fast walking speed is achieved.

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“…Taga et al [5] integrated feedbacks with neural oscillators for unpredicted environment. Yang et al [6], Shafii et al [7], and Yazdi et al [8] utilized TFS to formulate ZMP-based CPG model as the basic walking pattern of bipedal robot. Or [9] presented a hybrid CPG-ZMP control system for flexible spine humanoid robot.…”

Section: Introductionmentioning

confidence: 99%

“…Genetic Algorithm (GA) [6,13], Genetic Programming (GP) [14], Particle Swarm Optimization (PSO) [7], and Bee Algorithm [8] are adopted in searching the parameters of CPG model. Besides the above-mentioned techniques, there are still other gradient-free optimization techniques.…”

Section: Introductionmentioning

confidence: 99%

An Improved ZMP-Based CPG Model of Bipedal Robot Walking Searched by SaDE

Fung

Jing

2014

ISRN Robotics

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This paper proposed a method to improve the walking behavior of bipedal robot with adjustable step length. Objectives of this paper are threefold. (1) Genetic Algorithm Optimized Fourier Series Formulation (GAOFSF) is modified to improve its performance.(2) Self-adaptive Differential Evolutionary Algorithm (SaDE) is applied to search feasible walking gait. (3) An efficient method is proposed for adjusting step length based on the modified central pattern generator (CPG) model. The GAOFSF is modified to ensure that trajectories generated are continuous in angular position, velocity, and acceleration. After formulation of the modified CPG model, SaDE is chosen to optimize walking gait (CPG model) due to its superior performance. Through simulation results, dynamic balance of the robot with modified CPG model is better than the original one. In this paper, four adjustable factors ( hs,support , hs,swing , ks,support , and ks,swing ) are added to the joint trajectories. Through adjusting these four factors, joint trajectories are changed and hence the step length achieved by the robot. Finally, the relationship between (1) the desired step length and (2) an appropriate set of hs,support , hs,swing , ks,support , and ks,swing searched by SaDE is learnt by Fuzzy Inference System (FIS). Desired joint angles can be found without the aid of inverse kinematic model.

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Biped Walking Using Coronal and Sagittal Movements Based on Truncated Fourier Series

Cited by 22 publications

References 22 publications

A Fast and Stable Omnidirectional Walking Engine for the Nao Humanoid Robot

A Fast and Stable Omnidirectional Walking Engine for the Nao Humanoid Robot

Novel Stable Walking for Humanoid Robot Using Particle Swarm Optimization Algorithm

An Improved ZMP-Based CPG Model of Bipedal Robot Walking Searched by SaDE

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