razainno Goto Github PK

advance_robotic_analysis-of-cylindical-robot-

behavioral_cognitive_robtics-homework-exercises_soloution

computational-intelligence-slides-fall-2020

This is a course materials for the Fall 2020 class on Computational Intelligence (with a heavy focus on Linear Algebra and Convex Optimization tools, according to the needs of the student curriculum)

deep-learning-keras-tf-tutorial

Learn deep learning with tensorflow2.0, keras and python through this comprehensive deep learning tutorial series. Learn deep learning from scratch. Deep learning series for beginners. Tensorflow tutorials, tensorflow 2.0 tutorial. deep learning tutorial python.

design-of-boc-using-robotic-programming

home _work_2

design-of-optoelectronics-based-force-sensor

Sensors are widely used in many kinds of robotics systems for controlling, op- timizing, and monitoring the operation and the performance. They measure a large number of useful physical parameters. Among these, force and torque are primary measurements. This work presents a complete design and implementa- tion of the uni-axis force sensor. This force sensor is based on an optoelectronic sensor which is known as a light fork. This design can be used for various robotics applications to measure the force. The simplicity of design and its low cost, make it more feasible to measure the force applied by different robots by the deformation of a properly designed mechanical structure integrated into the actuation module. This force sensor provides good linearity and sensitivity for the applied force. The work contains the complete scheme of electronics schematics with PCB design. The electronics design contains the STM32f405 microcontroller, which has internal memory to save the calibration data. The mechanical design is also described in this work with proper dimension and length to construct the obstacle and case of the sensor. The design of the sen- sor can be modified for calibration and integration with the robotics module. The methodology of this work describes the basic working principle and also a proper mechanism to measure the force applied on the top surface of the sensor with the arrangement of four optoelectronics sensors.

environment-driven-exploration-in-reinforcement-learning

n reinforcement learning algorithm robot learn and explore the all possible action in all possible states in given environment .If noise is added to action vector , its doesn’t guarantee the to give the correct result for varied states. The main objective of this project is to study the behavior of robot in OpenAI Gym Environments by adding correlated noise . This include the introduction of pybullet environment and correlated noise, followed by methodology and results,which contain cons and pros of addition of correlated noise

food-detection-by-yolov2-with-transfer-learning

multi-object food detection system by DCNN and YOLOv2 strategy, with transferring features and class activation mapping, support mobilenet, mobilenetv2, resnet and darknet.

hw1-forwar-and-inverse-kinamatics-of-kuka-100-robot

hw3-joint-trajectory-

hw4-spline-analysis

hw5-forward_recursion-and-torque-trajectory

implementation-of-different-deep-learning-algorithm-for-images-detection

This repository contains the implementation of different deep learning algorithm in colab with all intruction

implementation-of-optimal-inverse-kinamatics-for-prrr-planner-manipulator-robotics-arm

This assignment present the Calculation of the inverse kinematics of PRRR planar robots for tracking from initial to desired point .The proposed method based on the choice of appropriate initial joint trajectories

internship_prjoect-interfacing-of-sensors-

master_thesis-force-sensor-pdf-file

This contain the pdf file of the master thesis with title "design of optoelctronics based force sensor "

mechanical-design-of-kuka-robot

Design and Working of KUKA-Robot in ROS

real-time-grasping-detection-using-neural-network

research-assistance-task

robot-grasp-detection

Detecting robot grasping positions with deep neural networks. The model is trained on Cornell Grasping Dataset. This is an implementation mainly based on the paper 'Real-Time Grasp Detection Using Convolutional Neural Networks' from Redmon and Angelova.

robot_urdf_e1

URDF for humanoid robot Asimo E1.

sattelite-segmentation-unet

This project is based on Unet architecture for segmentation process.

solar-inspection-preprint-paper

tripteron-robot-for-vjm-and-msa-model

uavs_q_learning_algorithm-for-drone-using-ros

This repository contains the simulation source code for implementing reinforcement learning aglorithms for autonomous navigation of ardone in indoor environments. Gazebo is the simulated environment that is used here