Humanoid robot walking control on inclined planes

The humanoid bipedal structure is suitable for a assitive robot functioning in the human environment. However, the bipedal walk is a difficult control problem. Walking just 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 feet 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. The average value of the body pitch angle is used as the inputs to the fuzzy logic system. A foot pitch orientation compensator implemented independently for the two feet complements the fuzyy controller. A 12-degrees-of-freedom (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 control method presented is successful in enabling the robot to climb slopes of 8.5 degrees (15 percent grade)

Biped robot walking control on inclined planes with fuzzy parameter adaptation

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-of-freedom (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)

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

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.&nbsp

Humanoid robot omnidirectional walking trajectory generation and control

Walking humanoid machines, once only seen or read in science fiction, became reality with the intensive research of the last four decades. However, there is a long way to go in the direction of technical achievements before humanoid robots can be used widely as human assistants. The design of a controller which can achieve a steady and stable walk is central in humanoid robotics. This control cannot be achieved if the reference trajectories are not generated suitably. The Zero Moment Point (ZMP) is the most widely used stability criterion for trajectory generation. The Center of Mass (CoM) reference can be obtained from the ZMP reference in a number of ways. A natural ZMP reference trajectory and a Fourier series approximation based method for computing the CoM reference from it, was previously proposed and published for the Sabanci University Robotics ReseArch Laboratory Platform (SURALP), for a straight walk. This thesis improves these techniques by modifying the straight walk reference trajectory into an omnidirectional one. The second contribution of this thesis is controller designs in order to cope with the changing slopes of the walking surface. The proposed controllers employ the trunk link rotational motion to adapt to the ground surface. A virtual pelvis link is introduced for the robots which do not posses roll and pitch axis in pelvis link. The proposed reference generation and control algorithms are tested on the humanoid robot SURALP. The experiments indicate that these methods are successful under various floor conditions

A study on automatic gait parameter tuning for biped walking robots

Automatic gait parameter tuning for biped walking robots is the subject of this thesis. The biped structure is one of the most versatile ones for the employment of mobile robots in the human environment. Their control is challenging because of their many DOFs and nonlinearities in their dynamics. Open loop walking with offline walk pattern generation is one of the methods for walking control. in this method the reference positions of the foot centers with respect to the body center are generated as functionals. Commonly, the tuning process for the trajectory generation is based on numerous trial and error steps. Obviously, this is a time consuming and elaborate process. In this work, online adaptation schemes for one of the trajectory parameters, "z-reference asymmetry", which is used for the compensation of uneven weight distribution of the robot in the sagittal plane, is proposed. In one of the approaches presented, this parameter is tuned online. As an alternative to parameter tuning, a functional learning scheme employing fuzzy identifiers is tested too. Fuzzy identifiers are universal function approximators. Fuzzy system parameters are adapted via back-propagation. An on-line tuning scheme for biped walk parameters however can only be successful if there is sufficient time for training without falling. The training might last hundreds of reference cycles. This implies that a mechanism for keeping the robot in continuous walk, even when the parameter settings are totally wrong, is necessary during training. In this work, virtual torsional springs which resist against deviations of the robot trunk angles from zero, are attached to the trunk center of the biped. The torques generated by the springs serve as the criteria for the tuning and help in maintaining a stable and a longer walk. The springs are removed after training. This novel approach can be applied to a wide range of control systems that involve parameter tuning. 3-D simulation techniques using C++ are employed for the model of a 12-DOF biped robot to test the proposed adaptive method. in order to visualize the walking, simulation results are animated using an OpenGL based animation environment. As a result of the simulations, a functional for the desired parameter, keeping the system in balance while walking, is generated

Trajectory planning for biped robot walking on uneven terrain – Taking stepping as an example

Abstract According to the features of movements of humanoid robot, a control system for humanoid robot walking on uneven terrain is present. Constraints of stepping over stairs are analyzed and the trajectories of feet are calculated by intelligent computing methods. To overcome the shortcomings resulted from directly controlling the robot by neural network (NN) and fuzzy logic controller (FLC), a revised particle swarm optimization (PSO) algorithm is proposed to train the weights of NN and rules of FLC. Simulations and experiments on different control methods are achieved for a detailed comparison. The results show that using the proposed methods can obtain better control effect

Humanoid Robots

For many years, the human being has been trying, in all ways, to recreate the complex mechanisms that form the human body. Such task is extremely complicated and the results are not totally satisfactory. However, with increasing technological advances based on theoretical and experimental researches, man gets, in a way, to copy or to imitate some systems of the human body. These researches not only intended to create humanoid robots, great part of them constituting autonomous systems, but also, in some way, to offer a higher knowledge of the systems that form the human body, objectifying possible applications in the technology of rehabilitation of human beings, gathering in a whole studies related not only to Robotics, but also to Biomechanics, Biomimmetics, Cybernetics, among other areas. This book presents a series of researches inspired by this ideal, carried through by various researchers worldwide, looking for to analyze and to discuss diverse subjects related to humanoid robots. The presented contributions explore aspects about robotic hands, learning, language, vision and locomotion

Bipedal humanoid robot control by fuzzy adjustment of the reference walking plane

The two-legged humanoid structure has advantages for an assistive robot in the human living and working environment. A bipedal humanoid robot can avoid typical obstacles at homes and offices, reach consoles and appliances designed for human use and can be carried in human transport vehicles. Also, it is speculated that the absorption of robots in the human shape into the human society can be easier than that of other artificial forms. However, the control of bipedal walk is a challenge. Walking performance on solely even floor is not satisfactory. The complications of obtaining a balanced walk are dramatically more pronounced on uneven surfaces like inclined planes, which are quite commonly encountered in human surroundings. The difficulties lie in a variety of tasks ranging from sensor and data fusion to the design of adaptation systems which respond to changing surface conditions. This thesis presents a study on bipedal walk on inclined planes with changing slopes. A Zero Moment Point (ZMP) based gait synthesis technique is employed. The pitch angle reference for the foot sole plane −as expressed in a coordinate frame attached at the robot body − is adjusted online by a fuzzy logic system to adapt to different walking surface slopes. Average ankle pitch torques and the average value of the body pitch angle, computed over a history of a predetermined number of sampling instants, are used as the inputs to this system. The proposed control method is tested via walking experiments with the 29 degreesof- freedom (DOF) human-sized full-body humanoid robot SURALP (Sabanci University Robotics Research Laboratory Platform). Experiments are performed on even floor and inclined planes with different slopes. The results indicate that the approach presented is successful in enabling the robot to stably enter, ascend and leave inclined planes with 15 percent (8.5 degrees) grade. The thesis starts with a terminology section on bipedal walking and introduces a number of successful humanoid robot projects. A survey of control techniques for the walk on uneven surfaces is presented. The design and construction of the experimental robotic platform SURALP is discussed with the mechanical, electronic, walking reference generation and control aspects. The fuzzy reference adjustment system proposed for the walk on inclined planes is detailed and experimental results are presented