55 research outputs found

    Development of a Locomotion and Balancing Strategy for Humanoid Robots

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    The locomotion ability and high mobility are the most distinguished features of humanoid robots. Due to the non-linear dynamics of walking, developing and controlling the locomotion of humanoid robots is a challenging task. In this thesis, we study and develop a walking engine for the humanoid robot, NAO, which is the official robotic platform used in the RoboCup Spl. Aldebaran Robotics, the manufacturing company of NAO provides a walking module that has disadvantages, such as being a black box that does not provide control of the gait as well as the robot walk with a bent knee. The latter disadvantage, makes the gait unnatural, energy inefficient and exert large amounts of torque to the knee joint. Thus creating a walking engine that produces a quality and natural gait is essential for humanoid robots in general and is a factor for succeeding in RoboCup competition. Humanoids robots are required to walk fast to be practical for various life tasks. However, its complex structure makes it prone to falling during fast locomotion. On the same hand, the robots are expected to work in constantly changing environments alongside humans and robots, which increase the chance of collisions. Several human-inspired recovery strategies have been studied and adopted to humanoid robots in order to face unexpected and avoidable perturbations. These strategies include hip, ankle, and stepping, however, the use of the arms as a recovery strategy did not enjoy as much attention. The arms can be employed in different motions for fall prevention. The arm rotation strategy can be employed to control the angular momentum of the body and help to regain balance. In this master\u27s thesis, I developed a detailed study of different ways in which the arms can be used to enhance the balance recovery of the NAO humanoid robot while stationary and during locomotion. I model the robot as a linear inverted pendulum plus a flywheel to account for the angular momentum change at the CoM. I considered the role of the arms in changing the body\u27s moment of inertia which help to prevent the robot from falling or to decrease the falling impact. I propose a control algorithm that integrates the arm rotation strategy with the on-board sensors of the NAO. Additionally, I present a simple method to control the amount of recovery from rotating the arms. I also discuss the limitation of the strategy and how it can have a negative impact if it was misused. I present simulations to evaluate the approach in keeping the robot stable against various disturbance sources. The results show the success of the approach in keeping the NAO stable against various perturbations. Finally,I adopt the arm rotation to stabilize the ball kick, which is a common reason for falling in the soccer humanoid RoboCup competitions

    Center of Pressure Feedback for Controlling the Walking Stability Bipedal Robots using Fuzzy Logic Controller

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    This paper presents a sensor-based stability walk for bipedal robots by using force sensitive resistor (FSR) sensor. To perform walk stability on uneven terrain conditions, FSR sensor is used as feedbacks to evaluate the stability of bipedal robot instead of the center of pressure (CoP). In this work, CoP that was generated from four FSR sensors placed on each foot-pad is used to evaluate the walking stability. The robot CoP position provided an indication of walk stability. The CoP position information was further evaluated with a fuzzy logic controller (FLC) to generate appropriate offset angles to be applied to meet a stable situation. Moreover, in this paper designed a FLC through CoP region's stability and stable compliance control are introduced. Finally, the performances of the proposed methods were verified with 18-degrees of freedom (DOF) kid-size bipedal robot

    Fractional Control of a Humanoid Robot Reduced Model with Model Disturbances

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    There is an open discussion between those who defend mass-distributed models for humanoid robots and those in favor of simple concentrated models. Even though each of them has its advantages and disadvantages, little research has been conducted analyzing the control performance due to the mismatch between the model and the real robot, and how the simplifications affect the controller's output. In this article we address this problem by combining a reduced model of the humanoid robot, which has an easier mathematical formulation and implementation, with a fractional order controller, which is robust to changes in the model parameters. This controller is a generalization of the well-known proportional-integral-derivative (PID) structure obtained from the application of Fractional Calculus for control, as will be discussed in this article. This control strategy guarantees the robustness of the system, minimizing the effects from the assumption that the robot has a simple mass distribution. The humanoid robot is modeled and identified as a triple inverted pendulum and, using a gain scheduling strategy, the performances of a classical PID controller and a fractional order PID controller are compared, tuning the controller parameters with a genetic algorithm.The research leading to these results has received funding from the ARCADIA project DPI2010-21047- C02-01, funded by CICYT project grant on behalf of Spanish Ministry of Economy and Competitiveness, and from the RoboCity2030-II-CM project (S2009/DPI-1559), funded by the Research and Development Work Programme of the Community of Madrid and cofunded by Structural Funds of the EU.Publicad

    ZMP based reference generation for a bipedal humanoid robot

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    Recent fifteen years witnessed fast improvements in the field of humanoid robotics. The human-like robot structure is more suitable to human environment with its supreme obstacle avoidance properties when compared with wheeled service robots. However, the walking control for bipedal robots is a challenging task due to their complex dynamics. Stable reference generation plays a very important role in control. Linear Inverted Pendulum Model (LIPM) and the Zero Moment Point (ZMP) criterion are applied in a number of studies for stable walking reference generation of biped walking robots. This thesis takes this main approach too. This thesis proposes a natural and continuous ZMP reference trajectory for a stable and human-like walk. Natural, human-like walking is obtained by ZMP trajectories which move forward under the sole of the support foot when the robot body is supported by a single leg. Robot center of mass trajectory is obtained from predefined ZMP reference trajectories by a Fourier series approximation method. The Gibbs phenomenon problem common with Fourier approximations of discontinuous functions is avoided by employing continuous ZMP references. Also, these ZMP reference trajectories, unlike many examples in the literature, possess pre-assigned single and double support phases, which are very useful in experimental tuning work. In this thesis, a method for generating a stepping sequence of finite number of steps is proposed too. The ZMP based reference generation strategy is applied on the full body humanoid robot SURALP designed at Sabanci University. Experimental results indicate that the proposed reference trajectory generation technique is successful

    Implementation of a robot platform to study bipedal walking

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    On this project, a modi cation of an open source, 3D printed robot, was implemented, with the purpose to create a more a ordable bipedal platform proper for studying Bipedal Walking algorithms. The original robot is a part of an open-source platform, called Poppy, that is formed from an interdisciplinary community of beginners and experts. One of the robots of this platform, is the Poppy Humanoid. The rigid parts of the Poppy Humanoid (as well as the rest of the Poppy platform robots) are 3D printed, a key factor of lowering the cost of a robot. The actuators used though, are expensive commercial DC-motors that increase the total cost of the robot drastically. This high cost of the actuators of Poppy, led this project to modify cheaper actuators while maintaining the same performance of their predecessors. Taking apart the components of the cheaper actuator, only the motor, the gears and the case that host them were kept, and a new design was made to control the motor and to meet the requirements set from the commercial motors. This new design of the actuator include a 12-bit resolution magnetic encoder to read the position of the shaft of the motor, a driver to run the motor, and also an embedded Arduino micro-controller. This feature of an Arduino as part of the actuator, gives the advantage over the commercial motor, as the user has the freedom to upload his own codes and to implement his own motor controllers. The result is a fully programmable actuator hosted on the same motor case. The size of this actuator though, is di erent from the commercial one. In order to mount the new actuators to the platform, Joan Guasch designed proper 3D printed parts. Apart of these parts, Joan also modi ed the leg design, in order to add another joint on the ankle (roll) as this Degree of Freedom (DoF) is important for Bipedal Walking algorithms and was missing from the original Poppy Humanoid leg design. The modi ed robot, is called Poppy-UPC and is a 12 DoF biped platform. For the communication between the motors and the main computer unit, a serial communication protocol was implemented based to the RS-485 standard. Multiple receivers (motors and sensors) can be connected to such a network in a linear, multi-drop con guration. The main computer unit of Poppy-UPC is an Odroid-C1 board. Essentially, this board is a Quad-core Linux computer fully compatible to run ROS. Odroid is acting as the master of the network and is gathering all the informations of the connected nodes, in order to publish them in ROS-topics. That way, the Poppy-UPC is connected to the ROS environment and ROS packages can be used for any further implementation with this platform. Finally, following the open-source spirit of the Poppy platform, all the codes and information are available at https://github.com/dimitris-zervas

    Push Recovery for Humanoid Robot in Dynamic Environment and Classifying the Data Using K-Mean

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    Push recovery is prime ability that is essential to be incorporated in the process of developing a robust humanoid robot to support bipedalism. In real environment it is very essential for humanoid robot to maintain balance. In this paper we are generating a control system and push recovery controller for humanoid robot walking. We apply different kind of pushes to humanoid robot and the algorithm that can bring a change in the walking stage to sustain walking. The simulation is done in 3D environment using Webots. This paper describes techniques for feature selection to foreshow push recovery for hip, ankle and knee joint. We train the system by K-Mean algorithm and testing is done on crouch data and tested results are reported. Random push data of humanoid robot is collected and classified to see whether push lie in safer region and then tested on given proposed system

    Implementation and design of new low-cost foot pressure sensor module using piezoelectric sensor in T-FLoW humanoid robot

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    Basically, human can sense the active body force trough the soles of their feet and can feel the position vector of zero moment point (ZMP) based on the center of pressure (CoP) from active body force. This behavior is adapted by T-FLoW humanoid robot using unique sensor which is piezoelectric sensor. Piezoelectric sensor has a characteristic which is non-continuous reading (record a data only a moment). Because of it, this sensor cannot be used to stream data such as flex sensor, loadcell sensor, and torque sensor like previous research. Therefore, the piezoelectric sensor still can be used to measure the position vector of ZMP. The idea is using this sensor in a special condition which is during landing condition. By utilizing 6 unit of piezoelectric sensor with a certain placement, the position vector of ZMP (X-Y-axis) and pressure value in Z-axis from action body force can be found. The force resultant method is used to find the position vector of ZMP from each piezoelectric sensor. Based on those final conclusions in each experiment, the implementation of foot pressure sensor modul using piezoelectric sensor has a good result (94%) as shown in final conclusions in each experiment. The advantages of this new foot pressure sensor modul is low-cost design and similar result with another sensor. The disadvantages of this sensor are because of the main characteristic of piezoelectric sensor (non-continuous read) sometimes the calculation has outlayer data

    Walking trajectory generation & control of the humanoid robot: suralp

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    In recent years, the operational area of the robots started to extend and new functionalities are planned for them in our daily environments. As the human-robot interaction is being improved, the robots can provide support in elderly care, human assistance, rescue, hospital attendance and many other areas. With this motivation, an intensive research is focused around humanoid robotics in the last four decades. However, due to the nonlinear dynamics of the robot and high number of degrees of freedom, the robust balance of the bipedal walk is a challenging task. Smooth trajectory generation and online compensation methods are necessary to achieve a stable walk. In this thesis, Cartesian foot position references are generated as periodic functions with respect to a body-fixed coordinate frame. The online adjustment of these parameterized trajectories provides an opportunity in tuning the walking parameters without stopping the robot. The major contribution of this thesis in the context of trajectory generation is the smoothening of the foot trajectories and the introduction of ground push motion in the vertical direction. This pushing motion provided a dramatic improvement in the stability of the walking. Even though smooth foot reference trajectories are generated using the parameter based functions, the realization of a dynamically stable walk and maintenance of the robot balance requires walking control algorithms. This thesis introduces various control techniques to cope with disturbances or unevenness of the walking environment and compensate the mismatches between the planned and the actual walking based on sensory feedback. Moreover, an automatic homing procedure is proposed for the adjustment of the initial posture before the walking experiments. The presented control algorithms include ZMP regulation, foot orientation control, trunk orientation control, foot pitch torque difference compensation, body pitch angle correction, ground impact compensation and early landing modification. The effectiveness of the proposed trajectory generation and walking control algorithms is tested on the humanoid robot SURALP and a stable walk is achieved

    Quasi-inverse pendulum model of 12 DoF bipedal walking

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    This paper presents modeling of a 12-degree of freedom (DoF) bipedal robot, focusing on the lower limbs of the system, and trajectory design for walking on straight path. Gait trajectories are designed by modeling of center of mass (CoM) trajectory and swing foot ankle trajectory based on stance foot ankle. The dynamic equations of motion of the bipedal robot are derived by considering the system as a quasi inverted pendulum (QIP) model. The direction and acceleration of CoM movement of the QIP model is determined by the position of CoM relative to the centre of pressure (CoP). To determine heel-contact and toe-off, two custom designed switches are attached with heel and toe positions of each foot. Four force sensitive resistor (FSR) sensors are also placed at the plantar surface to measure pressure that is induced on each foot while walking which leads to the calculation of CoP trajectory. The paper also describes forward kinematic (FK) and inverse kinematic (IK) investigations of the biped model where Denavit-Hartenberg (D-H) representation and Geometric-Trigonometric (G-T) formulation approach are applied. Experiments are carried out to ensure the reliability of the proposed model where the links of the bipedal system follow the best possible trajectories while walking on straight path
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