Walking Gait Learning for “T-FLoW” Humanoid Robot Using Rule-Based Learning

2021 ◽  
Author(s):  
Faiz Ulurrasyadi ◽  
Raden Sanggar Dewanto ◽  
Aliridho Barakbah ◽  
Dadet Pramadihanto
Keyword(s):  
Humanoid Robot ◽  
Rule Based ◽  
Walking Gait ◽  
Gait Learning

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.

scholarly journals Implementation and Integration of Fuzzy Algorithms for Descending Stair of KMEI Humanoid Robot

2020 ◽  
pp. 372-388
Author(s):  
Wulandari Puspita Sari ◽  
R. Sanggar Dewanto ◽  
Dadet Pramadihanto
Keyword(s):  
Humanoid Robot ◽  
Fuzzy Logic Controller ◽  
Integrated Control ◽  
Step Length ◽  
Smooth Transition ◽  
Double Support ◽  
Walking Gait ◽  
Single Support Phase ◽  
Support Phase ◽  
Double Support Phase

Locomotion of humanoid robot depends on the mechanical characteristic of the robot. Walking on descending stairs with integrated control systems for the humanoid robot is proposed. The analysis of trajectory for descending stairs is calculated by the constrains of step length stair using fuzzy algorithm. The established humanoid robot on dynamically balance on this matter of zero moment point has been pretended to be consisting of single support phase and double support phase. Walking transition from single support phase to double support phase is needed for a smooth transition cycle. To accomplish the problem, integrated motion and controller are divided into two conditions: motion working on offline planning and controller working online walking gait generation. To solve the defect during locomotion of the humanoid robot, it is directly controlled by the fuzzy logic controller. This paper verified the simulation and the experiment for descending stair of KMEI humanoid robot. 

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.

Omni-directional Walking Gait and Path Planning for Biped Humanoid Robot

2013 ◽  
Vol 12 (6) ◽  
pp. 1160-1167 ◽  
Author(s):  
Zai-jun Wang ◽  
Bao-fu Fang ◽  
Guo-qiang Shi
Keyword(s):  
Path Planning ◽  
Humanoid Robot ◽  
Walking Gait

scholarly journals Brain-Computer Interface-Based Humanoid Control: A Review

Sensors ◽  
2020 ◽  
Vol 20 (13) ◽  
pp. 3620 ◽  
Author(s):  
Vinay Chamola ◽  
Ankur Vineet ◽  
Anand Nayyar ◽  
Eklas Hossain
Keyword(s):  
Machine Learning ◽  
Humanoid Robot ◽  
Brain Computer Interface ◽  
Sensor Data ◽  
Computer Interface ◽  
Rule Based ◽  
Motor Disabilities ◽  
Brain Signals ◽  
Multi Sensor Data Fusion ◽  
Severe Motor

A Brain-Computer Interface (BCI) acts as a communication mechanism using brain signals to control external devices. The generation of such signals is sometimes independent of the nervous system, such as in Passive BCI. This is majorly beneficial for those who have severe motor disabilities. Traditional BCI systems have been dependent only on brain signals recorded using Electroencephalography (EEG) and have used a rule-based translation algorithm to generate control commands. However, the recent use of multi-sensor data fusion and machine learning-based translation algorithms has improved the accuracy of such systems. This paper discusses various BCI applications such as tele-presence, grasping of objects, navigation, etc. that use multi-sensor fusion and machine learning to control a humanoid robot to perform a desired task. The paper also includes a review of the methods and system design used in the discussed applications.

From standing balance to walking: A single control structure for a continuum of gaits

2019 ◽  
Vol 38 (14) ◽  
pp. 1695-1716
Author(s):  
Hamed Razavi ◽  
Salman Faraji ◽  
Auke Ijspeert
Keyword(s):  
Control Algorithm ◽  
Humanoid Robot ◽  
Control Structure ◽  
Standing Balance ◽  
Control Parameters ◽  
Bipedal Robot ◽  
Walking Gait ◽  
Small Set ◽  
Algorithm Framework ◽  
Stepping In Place

This article presents a control algorithm framework with which a bipedal robot can perform a variety of gaits by only modifying a small set of control parameters. The controller drives a number of variables, called non-emergent variables, to their desired trajectories resulting in a desired emergent walking gait. While the non-emergent variables remain the same independent of the gait, their desired trajectories are functions of a small set of control parameters that change as a function of the desired gait. This control algorithm has been tested on the humanoid robot COMAN, where different gaits including standing balance, stepping in place, periodic walking gaits with different velocities, as well as gait switching are demonstrated in experiments.

Dynamic walking of humanoid robot on flat surface using amplified LIPM plus flywheel model

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Abhishek Kumar Kashyap ◽  
Dayal R. Parhi
Keyword(s):  
Humanoid Robot ◽  
Center Of Mass ◽  
Humanoid Robots ◽  
Dynamic Walking ◽  
Turning Angle ◽  
Content Type ◽  
Walking Behavior ◽  
Walking Gait ◽  
Ant Lion Optimization ◽  
Travel Length

PurposeHumanoid robots have complicated dynamics, and they lack dynamic stability. Despite having similarities in kinematic structure, developing a humanoid robot with robust walking is quite difficult. In this paper, an attempt to produce a robust and expected walking gait is made by using an ALO (ant lion optimization) tuned linear inverted pendulum model plus flywheel (LIPM plus flywheel).Design/methodology/approachThe LIPM plus flywheel provides the stabilized dynamic walking, which is further optimized by ALO during interaction with obstacles. It gives an ultimate turning angle, which makes the robot come closer to the obstacle and provide a turning angle that optimizes the travel length. This enhancement releases the constraint on the height of the COM (center of mass) and provides a larger stride. The framework of a sequential locomotion planer has been discussed to get the expected gait. The proposed method has been successfully tested on a simulated model and validated on the real NAO humanoid robot.FindingsThe convergence curve defends the selection of the proposed controller, and the deviation under 5% between simulation and experimental results in regards to travel length and travel time proves its robustness and efficacy. The trajectory of various joints obtained using the proposed controller is compared with the joint trajectory obtained using the default controller. The comparison shows the stable walking behavior generated by the proposed controller.Originality/valueHumanoid robots are preferred over mobile robots because they can easily imitate the behaviors of humans and can result in higher output with higher efficiency for repetitive tasks. A controller has been developed using tuning the parameters of LIPM plus flywheel by the ALO approach and implementing it in a humanoid robot. Simulations and experiments have been performed, and joint angles for various joints are calculated and compared with the default controller. The tuned controller can be implemented in various other humanoid robots

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