Design and development of sit-to-stand trajectory and control of humanoid robot

Sitting position is an important feature in a humanoid robotic system as it is more stable when compared to standing position, resulting in less energy consumption since no actuator is needed to stabilize the robot. Sitting is crucial especially for humanoid robot in security and domestic robotics field where the robots are used for a long period. In order to return to standing position, sit to stand (STS) motion is needed. One of the main challenges in STS is during the lift-off; i.e. the moment when the robot’s thigh is lifted from the chair’s surface. During lift-off, a sudden change of the position of centre of mass (CoM) causes instability to the STS motion. Furthermore, the limitation of body and joint will exacerbate the problem by limiting the ability to move the CoM to appropriate position. Due to this issue, the first objective of this research is to develop and validate a system that autonomously able to identify a trajectory to transfer the CoM to an appropriate position before lift-off from any chair height. The method works by autonomously calculate the horizontal distance between the CoM and the support polygon. With the estimated distance, flexion of hip and ankle joints is made to bring the CoM into the support polygon. The arrangement of the motion is based on Alexander STS technique. Second objective is to develop and validate a control system to balance the robot from tumbling down during STS motion due to stability issue. The proposed control system employs the IF-THEN rules as the action selector. The rules are set based on CoP position and feedback from body’s angular direction in y-axis on sagittal plane. The rules set three variable i.e. HAT (Head-Arm-Torso) direction, HAT velocity, and proportional controller gain. To determine the gain for the proportional controller, the gain identification method implements the partitioning of CoP position into a number of regions. The coefficient at each region is set differently to increase the sensitivity of the controller. To verify the effectiveness of the proposed method, experiments using NAO robot were conducted. The stability of the robot was measured based on the position of Centre of pressure (CoP) within the feet area and the angle y reading. Results show that the robot was able to perform the STS motion when height of chair is varied from 9.95cm to 16.25cm. The CoP position also shows that the pressure point is always within the feet area. However, the system failed to perform the task when the height of chair is lower than 96.60% of the robot’s shank length due to the robot’s body limitation

Parameter estimation of Stochastic Logistic Model : Levenberg-Marquardt Method

In this paper, we estimate the drift and diffusion parameters of the stochas- tic logisticmodels for the growth of Clostridium Acetobutylicum P262 using Levenberg- Marquardt optimization method of non linear least squares. The parameters are esti- mated for five different substrates. The solution of the deterministic models has been approximated using Fourth Order Runge-Kutta and for the solution of the stochastic differential equations, Milstein numerical scheme has been used. Small values of Mean Square Errors (MSE) of stochastic models indicate good fits. Therefore the use of stochastic models are shown to be appropriate in modelling cell growth of Clostridium Acetobutylicum P26

Development Of Rubber Tire Gantry Crane (Prototype) Obstacles Avoidance Method Using A Single Sensor On Microcontroller Based

RTG crane is used to stack containers at the wharf. Because the size of the crane is too large and the operated at high place, it is nearly impossible for the operator to monitor the area under the crane. Currently, a pointing sensor system is installed but the crane still fails to stop if the obstacle is inside of the track due to low coverage of the pointing sensor system. In this paper, a new method is developed on a prototype system of RTG, to improve the current obstacle avoidance. The system is using is using servo motor to rotate an infrared sensor in order to cover the total area in the track. The results of new method is compared with the pointing sensor system and shown that the develop system by increasing the sensing area to three point or almost all the track area by rotating the infrared sensor 68” continuously and taking the possibility of obstacles outside the tracking area

Walking Motion Trajectory of Hip Powered Orthotic Device Using Quintic Polynomial Equation

In lower limb exoskeleton system walking motion profile generation, cubic polynomial is commonly used to generate smooth walking profile on flexion angle, velocity and acceleration data of three joint movements (ankle, knee and hip joints). However, cubic polynomial does not closely matched human motion. For this reason, a higher-order-polynomial i.e. quintic polynomial is proposed to gene- rate walking motion profile. Error analysis was conducted to measure how closely quintic polynomial could represent human walking motion profile. Result shows that quantic polynomial could closely represent human walking trajectory with maximum RMS error of 0.2607rad occurred during mid-swing phase

Monitored and controlled underwater scissor arm manipulator using Pixy camera

1120-1131Underwater vehicle manipulator system (UVMS) generally consists of a camera unit and robotic manipulator. Its main function is to replace human work in underwater manipulation tasks. Most commercially available manipulators are not designed for autonomous underwater vehicle (AUV) because the vehicle does not have sufficient power supply to drive these manipulators which are electro-hydraulically driven. A proposed solution is to invest in development of low power underwater manipulator to deepen studies in AUV. Thus, this research has an objective of developing an underwater manipulator for small scale AUV. In this research, the manipulator is used in an object recovery task. An acrylic scissor arm which is electro-mechanically driven is used as manipulator in this research. Permanent magnets are used as its end effector. A Pixy CMUcam5 vision sensor is paired with this manipulator to navigate the AUV and control the manipulator. The usage of planar pressure housing helps in reducing light refraction effect of underwater environment that may affect the sensor’s accuracy. From the simulation done using Solid Works, it is found out that type 316L stainless steel is the best choice for the manipulator developed. To evaluate the performance of the UVMS developed, a series of tests are carried out. Based on the results obtained, it is known that the system has high speed and consistency with minimum time delay between input and output. As long as an object has distinct colour signature from its background and its surrounding is clear and well illuminated, the Pixy vision sensor can detect that object regardless of the distance between the sensor and the object

Monitored And Controlled Underwater Scissor Arm Manipulator Using Pixy Camera

Underwater vehicle manipulator system (UVMS) generally consists of a camera unit and robotic manipulator. Its main function is to replace human work in underwater manipulation tasks. Most commercially available manipulators are not designed for autonomous underwater vehicle (AUV) because the vehicle does not have sufficient power supply to drive these manipulators which are electro-hydraulically driven. A proposed solution is to invest in development of low power underwater manipulator to deepen studies in AUV. Thus, this research has an objective of developing an underwater manipulator for small scale AUV. In this research, the manipulator is used in an object recovery task. An acrylic scissor arm which is electro-mechanically driven is used as manipulator in this research. Permanent magnets are used as its end effector. A Pixy CMUcam5 vision sensor is paired with this manipulator to navigate the AUV and control the manipulator. The usage of planar pressure housing helps in reducing light refraction effect of underwater environment that may affect the sensor’s accuracy. From the simulation done using Solid Works, it is found out that type 316L stainless steel is the best choice for the manipulator developed. To evaluate the performance of the UVMS developed, a series of tests are carried out. Based on the results obtained, it is known that the system has high speed and consistency with minimum time delay between input and output. As long as an object has distinct colour signature from its background and its surrounding is clear and well illuminated, the Pixy vision sensor can detect that object regardless of the distance between the sensor and the object

Design Analysis Of Compact Autonomous Railway Inspection Vehicle (CARIV)

The aim of this project is to reduce the occurrence of train derailment due to railway track defects to zero in the following years by increasing the efficiency of railway track inspection and railway track defects detection. Moreover, this project aims to reduce the need of railway track inspection workers to perform on-foot inspection at odd hours. All of these can be achieved by deploying the compact autonomous railway inspection vehicle (CARIV). The CARIV is equipped with ultrasonic sensors, which will be used to detect railway track defects. In addition, when railway track defects are detected, CARIV will take an image of the defective section of the railway track and send to the operator together with the GPS coordinates via email. CARIV will also be providing live video feedback to a browser so that the operator is able to perform visual checking for railway track defects undetectable by the ultrasonic sensor without having to perform on-foot inspection. This is to allow the operator to inspect the railway track defect in detail to determine the seriousness of the railway track damage. The final phase of this project is to test the system on fabricated railway track with defects

Model-Based Design (MBD) For Autonomous Underwater Vehicle

This project is to enhanced and upgraded a depth controller for Autonomous Underwater Vehicle (AUV) to submerge precisely at the certain depth. This poster demonstrated an AUV equipped with integrated sensor and depth controller based on the pressure sensing which able to continuously sending the depth data to controller. The depth Simulink Arduino algorithm is implemented on an Arduino Mega using ModelBased Design (MBD) with MATLAB and Simulink. MBD used to model, simulate and verify the Simulink control algorithm after obtained data through open-loop experiment test. Then, it deploys and tests the algorithm on the embedded AUV hardware. The focus was in controlling the AUV vertical trajectory as the AUV tried to remain stationary at the selected depth and consuming its rise time Tr, overshoot Os, and settling time Ts are minimized. The comparative study for the AUV depth-control by On-Off, Proportional Integral Derivative (PID) controller and Fuzzy Logic Controller (FLC) controllers. MBD has faster implementation with fewer coding error when deploy to AUV hardware