8 skills found
SinaMirrazavi / QP IK SolverQuadratic program based Inverse kinematic solver for mutli-robotic arms with respect to the kinematic and self-collision avoidance constraints
heethesh / Collision Avoidance SystemCollision Avoidance System for Self-Driving Vehicles by Delta Autonomy, Robotics Institute, CMU
nitronoid / CsbA cloth and soft body simulation library, using position based dynamics.
nbfigueroa / SCA Boundary LearningThis repository contains the necessary libraries, scripts and instructions to learn a Dual-Arm Self-Collision Avoidance Boundary.
Brain-Cog-Lab / RSNNThis repository uses a reward-modulated Spiking Neural Network to achieve self-organized, decentralized collision avoidance for drone swarm.
SinaMirrazavi / SCA Data ConstructionConstructing the data set for Self-Collision Avoidance (SCA) between two or more arms.
ranjithkumarpv / AutoRCCarThis project builds a self-driving RC car using Raspberry Pi, Arduino and open source software. Raspberry Pi collects inputs from a camera module and an ultrasonic sensor, and sends data to a computer wirelessly. The computer processes input images and sensor data for object detection (stop sign and traffic light) and collision avoidance respectively. A neural network model runs on computer and makes predictions for steering based on input images. Predictions are then sent to the Arduino for RC car control.
ohumkar / Self Driving CarA scaled down version of the self-driving system using OpenCV. The system comprises of - • Raspberry Pi with a webcam and an ultrasonic sensor as inputs, ◦ Steering using move in sdcar.py ◦ Stop sign detection using houghcircles and colour intensities ◦ Front collision avoidance using an ultrasonic sensor • l298N motor controller • project structure: *sdcar.py is a combination of all the following *lane_lines.py: step1.take the webcam feed and apply the canny edge algorithm to detect the edges step2. detect the lines in an edged image using houghlines step3. average the lines according to the slope step4.making points using slope step5. return right, left, camera and central line *sensor.py: distance measurement using input and output pins *sign.py: *detection of circles in image using hough circles *if the dominant colour in a square region around the circle is red then it is stop sign. *if the dominant colour in a square region around the circle is blue then there are 5 cases left, right, forward, forward and right or forward and left for this: • make the 3 zones of square regions the right , left, upper(for forward) • if the right zone is white and the other two are blue then the sum of RGB colour intensities in the right zone will be obviously greater than the other two zones then the sign is right similarly for others. Note : sign.py will work on following type of sign:
