Center of Pressure Feedback for Controlling the Walking Stability Bipedal Robots using Fuzzy Logic Controller (original) (raw)

IJERT-Design, Modeling and Analysis of Bipedal Walking Robot by Using Fuzzy Logic Controller

International Journal of Engineering Research and Technology (IJERT), 2013

https://www.ijert.org/design-modeling-and-analysis-of-bipedal-walking-robot-by-using-fuzzy-logic-controller https://www.ijert.org/research/design-modeling-and-analysis-of-bipedal-walking-robot-by-using-fuzzy-logic-controller-IJERTV2IS120359.pdf This paper describes the design, solid modeling and kinematic analysis of bipedal walking robot, which is developed through a strategy of balance control and movement of bipedal robot during its walk, it will also use fuzzy logic algorithm. The assumed motion for the bipedal robot is horizontal walking on a flat surface. The actuated joints are hip, knee and ankle joints which are driven by DC servomotors. The control signals produced by the fuzzy controllers are applied to the servomotors and then the response of the servomotors will led to the walking of the robot.

Fuzzy logic controller for stabilization of biped robot gait

ITM Web of Conferences, 2018

The article centers round the problem of stabilization of biped robot gait through smoothing out the jumps of first and second order derivatives of a biped robot control vector using the fuzzy logic approach. The structure of a composite Takagi-Sugeno fuzzy logic controller developed by the authors is presented. The simulation study of a robot gait with climbing an obstacle is carried out and the results provided in the article showed that the developed controller performed significantly better than the analytical formula model in terms of smoothing out the derivatives of the control vector.

Fuzzy Logic-Based Controller for Bipedal Robot

Applied Sciences, 2021

In this paper, the problem of controlling a human-like bipedal robot while walking is studied. The control method commonly applied when controlling robots in general and bipedal robots in particular, was based on a dynamical model. This led to the need to accurately define the dynamical model of the robot. The activities of bipedal robots to replace humans, serve humans, or interact with humans are diverse and ever-changing. Accurate determination of the dynamical model of the robot is difficult because it is difficult to fully and accurately determine the dynamical quantities in the differential equations of motion of the robot. Additionally, another difficulty is that because the robot’s operation is always changing, the dynamical quantities also change. There have been a number of works applying fuzzy logic-based controllers and neural networks to control bipedal robots. These methods can overcome to some extent the uncertainties mentioned above. However, it is a challenge to bui...

Fuzzy control for bipedal robot considering energy balance

Contemporary Engineering Sciences, 2018

This paper shows the development of a vertical balance control system on a bipedal robot prototype of 10 DOF (degrees of freedom), belonging to the ARMOS research group. The control system was simulated off-line in order to observe the response time, and then implemented in a microcontroller. This document describes the process that was carried out to achieve the objective, from the adaptation of the plant, to the results of the simulations and the tests carried out, where it is evident how an articulation is taken to its position of balance.

Neuro-Fuzzy Gait Generator for a Biped Robot

2012

ABSTRACT: The control of walking robots has improved dramatically over the last few years. Several methodologies have been developed for this. As one of them, in this work, we used fuzzy logic controller that generates angular of the knees in order to active a desired position of the center of mass. We present a fuzzy gait generator, FGG, that generates the angular trajectories of a biped robot. The FGG, is a neuro-fuzzy gait generator that used a classical geometric model of a 5 segments representation and replicated its comportment.

Biped Robot Walking Control on Inclined Planes with Fuzzy Parameter Adaptation

IFAC Proceedings Volumes, 2010

The bipedal structure is suitable for a robot functioning in the human environment, and assuming assistive roles. However, the bipedal walk is a poses a difficult control problem. Walking on even floor is not satisfactory for the applicability of a humanoid robot. This paper presents a study on bipedal walk on inclined planes. A Zero Moment Point (ZMP) based reference generation technique is employed. The orientation of the upper body is adjusted online by a fuzzy logic system to adapt to different walking surface slopes. This system uses a sampling time larger than the one of the joint space position controllers. A newly defined measure of the oscillatory behavior of the body pitch angle and the average value of the pelvis pitch angle are used as inputs to the fuzzy adaptation system. A 12-degrees-offreedom (DOF) biped robot model is used in the full-dynamics 3-D simulations. Simulations are carried out on even floor and inclined planes with different slopes. The results indicate that the fuzzy adaptation algorithms presented are successful in enabling the robot to climb slopes of 5.6 degrees (10 percent).

Fuzzy Logic Velocity Control of a Biped Robot Locomotion and Simulation

International Journal of Advanced Robotic Systems, 2012

In this paper, fuzzy logic velocity control of a biped robot to generate gait is studied. The system considered in this study has six degrees of freedom with hip, knee and ankle joints. The joint angular positions are determined utilizing the Cartesian coordinate information of the joints obtained by using camera captured data of the motion. The first derivatives of the calculated joint angular positions are applied as the reference angular velocity input to the fuzzy controllers of the joint servomotors to generate a gait motion. The assumed motion for the biped robot is horizontal walking on a flat surface. The actuated joints are hip, knee and ankle joints which are driven by DC servomotors. The calculated angular velocities of the joints from camera captured motion data are utilized to get the driving velocity functions of the model as sine functions. These functions are applied to the fuzzy controller as the reference angular velocity inputs. The control signals produced by the fuzzy controllers are applied to the servomotors and then the response of the servomotor block is introduced as an input to the SimMechanics model of the biped robot. The simulation results are provided which evaluate the effectiveness of the fuzzy logic controller on joint velocities to generate gait motion.

Neuro-Fuzzy Algorithm For A Biped Robotic System

2008

This paper summaries basic principles and concepts of intelligent controls, implemented in humanoid robotics as well as recent algorithms being devised for advanced control of humanoid robots. Secondly, this paper presents a new approach neuro-fuzzy system. We have included some simulating results from our computational intelligence technique that will be applied to our humanoid robot. Subsequently, we determine a relationship between joint trajectories and located forces on robot-s foot through a proposed neuro-fuzzy technique.

Implementation of a Hierarchical fuzzy controller for a biped robot

2014

In this paper the design of a control system for a biped robot is described. Control is specified for a walk cycle of the robot. The implementation of the control system was done on Matlab Simulink. In this paper a hierarchical fuzzy logic controller (HFLC) is proposed to control a planar biped walk. The HFLC design is bio-inspired from human locomotion system. The proposed method is applied to control five links planar biped into free area and without obstacles.

Dynamic Control Strategy of a Biped Inspired from Human Walking

Intelligent Engineering Systems through Artificial Neural Networks Volume 18, 2008

In this paper, we show that a biped robot can walk dynamically using a simple control technique inspired from human locomotion. We introduce four critical angles that affect robot speed and step length. Our control approach consists in tuning the PID parameters of each joint in each walking phase for introducing active compliance and then to increase stability of the walk. We validated the control approach to a dynamic simulation of our 14DOF biped called ROBIAN. A comparison with human walking is presented and discussed. We prove that we can maintain robot stability and walk cycle's repetition without referencing a predefined trajectory or detecting the center of pressure. Results show that the walk of the biped is very similar to human one. A power consumption analysis confirms that our approach could be implemented on the real robot ROBIAN.