Advance Research on Foot & Ankle for the (GUCnoid2.0)
Design and Control for the Foot Robotic lower limb prosthetic for Human/Humanoid Locomotion
Robotic prostheses have the potential to significantly improve mobility for people with lower-limb amputation. Humans exhibit complex responses to mechanical interactions with these devices, however, and computational models are not yet able to predict such responses meaningfully. Experiments therefore play a critical role in development, but have been limited by the use of product like prototypes, each requiring years of development and specialized for a narrow range of functions. In this project we describe a robotic ankle–foot prosthesis system that enables rapid exploration of a wide range of dynamical behaviors in experiments with human subjects.
Design and Dynamic Analysis of a Back Driven Two-Stage Cycloidal Drive for Robotic Joints Applications
Cycloidal gear reducers (or cycloidal drives) are high-efficiency and high-speed reduction ratio motion and torque transmission devices. They are commonly used in equipment where precise output and large drive payloads are needed. Recently, with the increasing demand of high efficiency and high-speed reduction and torque ratio transmission devices in industry, applications of cycloidal gear reducers have become popular in the automation field as robotics, machine tools, and automatic machinery. Nonetheless, compared to involute gear drives, manufacture of cycloidal gear reducers requires a more dedicated process because of the non-standard characteristics of the devices.
Machine Learning Approaches for Activity Recognition for the Foot Robotic lower limb prosthetic for Human/Humanoid Locomotion
There are several machine learning approaches that can be used for activity recognition in a foot robotic lower limb prosthetic for human/humanoid locomotion. Some common approaches include; Supervised Learning, Unsupervised Learning, Reinforcement Learning or Deep Learning. It's important to note that the choice of approach will depend on the availability of labeled data, the complexity of the sensor readings, and the desired level of control over the prosthetic.
Simulation and implementation of Brushless DC motor driver PCB using Field oriented control for Robotic Joints Applications
BLDC motors have numerous advantages over regular DC motors but they have one big disadvantage, the complexity of control. Even though it has become relatively easy to design and manufacture PCBs and create our own hardware solutions for driving BLDC motors the proper low-cost solutions are yet to come. One of the reasons for this is the apparent complexity of writing the BLDC driving algorithms, Field oriented control (FOC) being an example of one of the most efficient ones. The solutions that can be found on-line are almost exclusively very specific for certain hardware. FOC algorithm implementation requires real time feedback of the currents and rotor position. Measure the current and position by using sensors. You can also use sensorless techniques that use the estimated feedback values instead of the actual sensor-based measurements.
Modeling design and fabrication of tension-controlled high speed and accuracy BLDC coil stator winding Machine for for Robotic Joints Applications
A brushless DC electric motor (BLDC motor or BL motor), also known as an electronically commutated motor (ECM or EC motor) or synchronous DC motor, is a synchronous motor using a direct current (DC) electric power supply. It uses an electronic controller to switch DC currents to the motor windings producing magnetic fields which effectively rotate in space and which the permanent magnet rotor follows. The controller adjusts the phase and amplitude of the DC current pulses to control the speed and torque of the motor. It is required to design and control a winding machine for the motor BLDC armature stator coil winding. The automatic stator winder adopts needle winding method. Each action cycle will wind 1 or 2 BLDC stator at the same time, managing high production efficiency. And the motor needle winder equipped with the servo control system, able to diagnose the fault, count the output etc. The other function such as auto winding, multi-diameter wires winding, auto indexing, auto skip slot and winding speed should be be programmed, easy for operation and maintenance.
Vision and Sounds Recognition for the (GUCnoid2.0)
A Real-Time Vision System Based on Motion Planning for Humanoid Robots Used in the Gain Scheduling Technique Based on the Animatronics Mechanisms
This project presents a real-time vision-based behaviors for complex robots such as humanoids. The underlying main scientific question structuring this work is the following: “What are the decisional processes which make possible for a humanoid robot to generate motion in real-time based upon visual information?” In soccer humans can decide to kick a ball while running and when all the other players are constantly moving. When recast as an optimization problem for a humanoid robot, finding a solution for such behavior is generally computationally hard. For instance, the problem of visual search consider in this work is NP-complete (nondeterministic polynomial-time complete).
Designing a Voice Recognition System for Humanoid Robots Interactions with People based on the Sound Source Localization System
In this project, we present a novel approach for designing a voice recognition system for humanoid robots interactions with people based on a sound source localization system. The proposed system utilizes advanced sound source localization algorithms to accurately identify the location of a speaker, and then uses this information to improve the performance of the voice recognition system. The proposed system is designed to work in real-world environments, where the background noise and reverberation can affect the performance of the voice recognition system. The system is evaluated through simulations and experiments on a humanoid robot platform, showing significant improvement in the accuracy and robustness of the voice recognition system.
Continuous Rotary power transducer design using Rotary Variable Differential Transformer (RVDT) for Robotics Applications
A Rotary Variable Differential Transformer (RVDT) is an electromechanical transducer that provides a variable alternating current (AC) output voltage that is linearly proportional to the angular displacement of its input shaft. When energized with a fixed AC source, the output signal is linear within a specified range over the angular displacement. RVDT’s utilize brushless, non-contacting technology to ensure long-life and reliable, repeatable position sensing with infinite resolution. Such reliable and repeatable performance assures accurate position sensing under the most extreme operating conditions. The circuit diagram of RVDT, consists of one primary and two secondary winding. The physical parameters of the RVDT core and design aspects are selected in such a way that the coil generates angular displacement linearly with respect to the induced mutual inductance between the primary and individual secondary coils. It is also called a passive transducer since it is powered from an external electrical source and converts angular displacement into electrical signals.
Advance Research on The Lower Section of the (GUCnoid2.0)
Active Suspension System Using the Dynamic Stability Strategy for the Humanoid Legged Robots with Impact Disturbance Rejection
In this project, we present an approach for an active suspension system using a dynamic stability strategy for humanoid legged robots with impact disturbance rejection. The proposed system utilizes advanced control algorithms and dynamic stability strategies to improve the stability and performance of the humanoid legged robots during walking and running, one of these controller is H-infinity Controller. The active suspension system is designed to actively adjust the robot's center of mass in response to external disturbances such as uneven terrain, obstacles or impact. The proposed system is also designed to reject disturbances and maintain the balance of the robot, which is crucial for its stability and safety.
Bipedal Robotic Walking Control Algorithm Using Gait Analysis for Humanoid Robot
In this project, we are going to build and fabricate a design for the bipedal robot then based on the controller that we will use, we will make a performance evaluation of a bipedal robot that utilizes the Hybrid Leg mechanism. It is a leg mechanism that achieves 6 DOF with a combined structure of serial and parallel mechanism. It is designed to have a light structural inertia and large workspace for agile bipedal locomotion.
Control of Dynamic Legged Locomotion Using Gain Scheduling Technique Vs. Modal Reference Adaptive Approach
In this work, we present a comparative study of two advanced control techniques for dynamic legged locomotion: gain scheduling and modal reference adaptive approach. The gain scheduling technique is based on adjusting the controller's gain parameters based on the robot's current operating conditions, while the modal reference adaptive approach is based on adjusting the controller's reference model based on the robot's current operating conditions. Both techniques are designed to improve the stability and performance of the robot during walking and running. The performance of both techniques is evaluated through simulations and experiments on a legged robot platform, and the results are compared to evaluate the effectiveness and efficiency of each approach.
Soft Safe Robot Actuators (Artificial Muscles) for Humanoid Robot Inspired by Human Bicep Muscles Using an Origami Soft Actuator
Humanoid robots are a relatively new sub category of robots that is characterized with human-like appearance, movement and a design that allows them to carry out a wide array of varying tasks in environments that would usually be suited for humans. When the robots are going work around humans, they will have to be softer and safer. Our Team at the ARAtronics Research Center has designed a new actuator with that in mind. Its movements are similar to those of a human bicep muscle, using a new way to automate soft rubber beams. Like real muscles, the actuators are soft, shock-absorbing, and pose no danger, according to the researchers.
Trajectory Tracking Control for a Soft Robotic Actuator Based on Origami Mechanism
When most people picture robots, they see machines with rigid parts. In this project the robots will be developed are soft, with parts made from deformable plastics and rubber. Soft robots are safer to operate around people and are ideally suited to carry out a variety of tasks that their traditionally rigid cousins can’t, including moving snake-like through confined spaces. But their ability to bend in many axes and change their shape make them unable to carry heavy loads, which limits their utility. So that a new class of variable-stiffness robots that have which have rigidity and softness. This innovative designs draw on the ancient art of paper folding, known as origami.
Control and Stability in the Torso Mechanism for the (GUCnoid2.0)
Tracking Control for a Tendon-Driven Continuum Robot with Embedded Sensors Which Acts as Torso for the Humanoid Robot
The purpose of this project is to present a novel hybrid pre-tension mechanism for continuum manipulators to prevent wire slack and improve continuum robot payload capacity, as well as to present a new method to control continuum manipulators’ shape. The Continuum robot, aka snake robot, aka elephant's trunk robot with 3DOF. It uses three servo motors to pull three strings. In this project we will used compression spring in the centre of the trunk to provide rigidity. This robot looks really strange, almost disgusting
Motion Analysis Stability Study Kinematic Modelling and Control for the Continuum Flexible Spine Torso Mechanism of Humanoid Robot
In this work, we present a comprehensive study of motion analysis, stability, kinematic modeling and control for the continuum flexible spine torso mechanism of humanoid robots. The proposed research combines various techniques and methodologies to achieve a better understanding of the dynamics of the flexible spine mechanism, and to develop control strategies that improve the stability and performance of the robot. The motion analysis includes the study of the kinematic and dynamic behavior of the flexible spine mechanism, while the stability study focuses on the identification and analysis of the stability regions of the robot.
Stability Control of the Flexible Spine for Humanoid Robot Using Soft Structure that modelled as Dual-axis Reaction Wheel Pendulum based on Fuzzy Logic Controller
Most traditional robotic mechanisms feature inelastic joints that are unable to robustly handle large deformations and off-axis moments. As a result, the applied loads are transferred rigidly throughout the entire structure. The disadvantage of this approach is that the exerted leverage is magnified at each subsequent joint possibly damaging the mechanism. In this project, we will work on two lightweight, elastic, bio-inspired tensegrity robotic mechanism adapted from prior static models which mitigate this danger while improving their mechanism’s functionality.
Stability Study and Control the Torso Mechanism of Humanoid Robot Based on the Linear Quadratic Regulator Approach
In this work, we present a stability study and control approach for the torso mechanism of humanoid robots based on the linear quadratic regulator (LQR) method. The proposed control approach utilizes the LQR technique to design a controller that improves the stability of the robot's torso mechanism and to optimize the performance of the robot. The stability study is focused on the identification and analysis of the stability regions of the robot. The LQR controller is designed to optimize the stability and performance of the robot's torso mechanism by adjusting the control inputs based on the robot's current state.
Motion Analysis and Stability Study on the Torso Mechanism of Humanoid Robot while Using Tensegrity Spine
In this work, we present a motion analysis and stability study on the torso mechanism of a humanoid robot while using a tensegrity spine. The proposed study focuses on the dynamics and stability of the robot's torso mechanism, which is based on a tensegrity spine. The motion analysis includes the study of the kinematic and dynamic behavior of the tensegrity spine mechanism, while the stability study focuses on the identification and analysis of the stability regions of the robot. The results from the analysis are used to understand the behavior of the tensegrity spine mechanism under different operating conditions and to develop control strategies that improve the stability and performance of the robot.
Stability Study and Control the Torso Mechanism of Humanoid Robot Based on Fuzzy Logic Controller
In this work, we present a stability study and control approach for the torso mechanism of humanoid robots based on fuzzy logic controller (FLC). The proposed control approach utilizes the FLC technique to design a controller that improves the stability of the robot's torso mechanism and optimize the performance of the robot. The stability study is focused on the identification and analysis of the stability regions of the robot. The FLC is designed to handle the nonlinearity and uncertainties present in the dynamics of the torso mechanism of the humanoid robot, by using fuzzy logic rules that map the inputs to the control outputs.
Optimization of the Smart Tendons for Soft Tensegrity Robots Which Acts as Torso for the Humanoid Robot
In this work, we present a novel approach for optimization of the smart tendons for soft tensegrity robots which act as the torso for humanoid robots. The proposed system utilizes optimization techniques to improve the performance and efficiency of the smart tendons, which are responsible for the movement of the robot's torso. The optimization process takes into account the dynamics of the soft tensegrity structure and the desired motion of the robot, and uses this information to generate the appropriate tension force in the smart tendons.
Advance Research on The Upper Section of the (GUCnoid2.0)
Design A Compliance Control for the Upper Limb Robotic System for Humanoid Robot
Compliance control is highly relevant to human safety in human–robot interaction (HRI). This project presents some various compliance control techniques. This project is aimed to provide a good background knowledge for new researchers and highlight the current hot issues in compliance control research. Active compliance, passive compliance, adaptive and reinforcement learning-based compliance control techniques are discussed. This project provides a comprehensive literature survey of compliance control keeping in view physical human robot interaction (pHRI) e.g., passing an object, such as a cup, between a human and a robot. Compliance control may eventually provide an immediate and effective layer of safety by avoiding pushing, pulling or clamping in pHRI. Emerging areas such as soft robotics, which exploit the deformability of biomaterial as well as hybrid approaches which combine active and passive compliance are also highlighted. Also we need to use the Modal Reference Adaptive Control (MRAC) as a control alternative technique.
Design an Impedance Controller Based on Model Reference Adaptive Control for the Upper Limb Robotic System of Humanoid Robot
In this work, we present a novel approach for designing an impedance controller based on model reference adaptive control (MRAC) for the upper limb robotic system of a humanoid robot. The proposed system utilizes MRAC to achieve a compliant behavior of the robot's upper limb, allowing it to adapt to the environment and interact with objects in a natural way. The impedance controller is designed to provide a balance between the stability and flexibility of the robot's upper limb, allowing it to perform a wide range of tasks while avoiding singularities and other issues that can affect the robot's performance.
Design a Feedback Controller for the Reaction Force Estimation on the the Upper Limb Robotic System of Humanoid Robot
In this work, we present a novel approach for designing a feedback controller for the reaction force estimation on the upper limb robotic system of a humanoid robot. The proposed system utilizes advanced control techniques to achieve accurate estimation of the reaction forces on the robot's upper limb, allowing it to interact with objects in a natural way while avoiding collisions. The feedback controller is designed to provide a balance between the stability and flexibility of the robot's upper limb, allowing it to perform a wide range of tasks while avoiding singularities and other issues that can affect the robot's performance. The proposed control system is also designed to be easily integrated with other control and monitoring systems, providing a seamless and robust control of the robot's upper limb.