3D Printed Soft Robotic Hand

Soft robotics is an emerging industry, largely dominated by companies which hand mold their actuators. Our team set out to design an entirely 3D printed soft robotic hand, powered by a pneumatic control system which will prove both the capabilities of soft robots and those of 3D printing. Through research, computer aided design, finite element analysis, and experimental testing, a functioning actuator was created capable of a deflection of 2.17” at a maximum pressure input of 15 psi. The single actuator was expanded into a 4 finger gripper and the design was printed and assembled. The created prototype was ultimately able to lift both a 100-gram apple and a 4-gram pill, proving its functionality in two prominent industries: pharmaceutical and food packing

The generation of dual wavelength pulse fiber laser using fiber bragg grating

A stable simple generation of dual wavelength pulse fiber laser on experimental method is proposed and demonstrated by using Figure eight circuit diagram. The generation of dual wavelength pulse fiber laser was proposed using fiber Bragg gratings (FBGs) with two different central wavelengths which are 1550 nm and 1560 nm. At 600 mA (27.78 dBm) of laser diode, the stability of dual wavelength pulse fiber laser appears on 1550 nm and 1560 nm with the respective peak powers of -54.03 dBm and -58.00 dBm. The wavelength spacing of the spectrum is about 10 nm while the signal noise to ratio (SNR) for both peaks are about 8.23 dBm and 9.67 dBm. In addition, the repetition rate is 2.878 MHz with corresponding pulse spacing of about 0.5 μs, is recorded

RealAnt: An Open-Source Low-Cost Quadruped for Research in Real-World Reinforcement Learning

Current robot platforms available for research are either very expensive or unable to handle the abuse of exploratory controls in reinforcement learning. We develop RealAnt, a minimal low-cost physical version of the popular 'Ant' benchmark used in reinforcement learning. RealAnt costs only $410 in materials and can be assembled in less than an hour. We validate the platform with reinforcement learning experiments and provide baseline results on a set of benchmark tasks. We demonstrate that the TD3 algorithm can learn to walk the RealAnt from less than 45 minutes of experience. We also provide simulator versions of the robot (with the same dimensions, state-action spaces, and delayed noisy observations) in the MuJoCo and PyBullet simulators. We open-source hardware designs, supporting software, and baseline results for ease of reproducibility

Electronic CVT - Controls

The following document outlines the design process, manufacturing, and testing of the control system for an electronically controlled continuously variable transmission (ECVT). This control system was integrated into the custom designed and manufactured mechanical transmission system created in parallel by another senior project group. The transmission was designed for use in the Cal Poly Baja SAE vehicle. Through researching customer needs, competition requirements, previous and alternate CVT designs, and vehicle characteristics, we were able to determine the requirements and specifications for our unique system. Input, output, speed, and durability requirements guided our hardware selection. The primary components which comprised our system include an alternator and regulator, a custom circuit board, rotary encoders and hall effect sensors, brushed DC motors, lead screws, and a custom system enclosure; further details are included in the Final Design section of this report. With the knowledge of our vehicle characteristics, actuation mode, and inputs, a system model determined that a standard proportional + integral action (PI) controller would be sufficient to obtain the speed and accuracy demanded by our customer needs. Electrical components were assembled, tested, and programmed on a prototyping breadboard, and a custom printed circuit board (PCB) was outsourced for manufacture following qualification of our prototype. The final production board was bench tested with the mechanical CVT system to ensure it met all customer and design requirements. Furthermore, the enclosure was tested to ensure the safety and durability of the electrical systems. Planning and timing mismanagement between our team, the mechanical design team, and Cal Poly SAE Baja team, in conjunction with controls specific setbacks, resulted in the final combined system remaining untested on the Baja vehicle. This project is being continued by a new senior project group which will continue to test and improve upon the current system during the 2019-2020 academic year

Real-time Energy Management System of Battery-Supercapacitor in Electric vehicles

This thesis presents the design, simulation and experimental validation of an Energy Management System (EMS) for a Hybrid Energy Storage System (HESS) composed of lithium ion batteries and Supercapacitors (SCs) in electric vehicles. The aim of the EMS is to split the power demand considering the weaknesses and strengths or the power sources. The HESS requires an EMS to determine power missions for the battery and SC in real time, where the SC is commanded to assist the battery during high power demand and recover the energy generated during braking. Frequency sharing techniques have been proposed by researchers to achieve this objective, including the Discrete Wavelet Transform (DWT) and conventional filtration methods (low and high pass filters). However, filtration approaches can introduce delay (milliseconds to tens of seconds) in the frequency components which undermines the hybridisation advantages. Hence, the selection of the filtration technique and filter design are crucial to the system's performance. Researchers have proposed power demand prediction methodologies to deal with time delay, however, the advantages and drawbacks of using such methods have not been investigated thoroughly, particularly whether time delay compensation and its inherent prediction error improves the system performance, efficiency, and timely SC contribution during the motoring and braking stages. This work presents a fresh perspective to this research field by introducing a novel approach that deals with delay without complicated prediction algorithms and improves the SC contribution during the motoring and braking stages while reducing energy losses in the system. The proposed EMS allows the SC to provide timely assistance during motoring and to recover the braking energy generated. A charging strategy controls energy circulation between the battery and SC to keep the SC charge availability during the whole battery discharge cycle. The performance and efficiency of the HESS is improved when compared to the traditional use of conventional filtration techniques and the DWT. Results show that the proposed EMS method improves the energy efficiency of the HESS. For the US06 driving cycle, the energy efficiency is 91.6%. This is superior to the efficiency obtained with an EMS based on a high pass filter (41.3%), an EMS based on DWT high frequency component (30.3%) and an EMS based on the predicted DWT high frequency component (41%)

Prototype Of Mask Recognition And Body Temperature In Real Time With Amg8833 Thermal Cam Sensor For Covid-19 Early Warning Based On Minicomputer

On April 19, 2020, the Republican Covid Task Force declared that the Covid-19 pandemic was a national disaster in Indonesia. At that time it was confirmed that there were 6575 cases and an increase of 5.23% compared to the previous day, then there were 5307 people in treatment which increased by 5.55% compared to the previous day, it was reported that 582 people died, which increased by 8.79 % compared to the previous day, and 686 recovered patients. WHO reports that the case fatality rate (CFR) or the death rate of Covid-19 cases in Indonesia reached 8.3%, which is twice the world's CFR. In this study, the main focus is to detect masks and body temperature used by visitors with various variations of masks on the market today, and next is to control the servo motor according to the detection conditions whether using a mask in real-time. Based on research on the system that has been tested, it shows that the components used to generate heat are very effectively used and can work as expected, and the MobilenetV2 method applied to the Raspberry Pi as the brain of the system can work as expected and has an accuracy rate of 99%. The AMG8833 sensor can read effectively at a maximum distance of 30 cm, the temperature reading deviation level is 0.1⁰C

A Portable Implementation on Industrial Devices of a Predictive Controller Using Graphical Programming

This paper presents an approach for developing an Extended Prediction Self-Adaptive Controller employing graphical programming of industrial standard devices, for controlling fast processes. For comparison purposes, the algorithm has been implemented on three different FPGA (Field Programmable Gate Arrays) chips. The paper presents research aspects regarding graphical programming controller design, showing that a single advanced control application can run on different targets without requiring significant program modifications. Based on the time needed for processing the control signal and on the application, one can efficiently and easily select the most appropriate device. To exemplify the procedure, a conclusive case study is presented