Nikhil619

Robotics, Deep learning, Machine learning, Reinforcement learning, Artificial Intelligence, Mechatronics.

TENSRAI

Pinned Repositories

Application-of-Yolo-in-real-time---in-autonomous-driving
the model can be used in self-driving cars or robots
Language:Python2 1 00
cnn-with-pytorch
Simple Convolutional-Neural-Network for a multiclass classification problem using PyTorch... work in progress!
Language:Jupyter Notebook10
Complete-navigation-system-for-a-mobile-robot-GA-tech-
Language:MATLAB1 1 00
Direction_of_motion_control_of_a_pi_robot_by_hand_movements
This robot can be controlled with hand movements which makes the control of the robot easier and more convenient.
Language:Jupyter Notebook1 1 00
Hybrid-Artificial-Potential-Fields-Algorithm-for-hexarotor
Language:Python3 1 00
Navigation-of-an-autonomous-rover-in-an-unknown-environment-by-localization-and-mapping
Language:Jupyter Notebook11
Path-planning-of-a-quadrotor-or-a-mobile-robot-using-RRTs-with-A-algorithm-
Language:Python1 1 00
Planning-and-controlling-the-motion-of-a-mobile-manipulator-simulated-in-V-REP-on-a-kuka-youbot-
Language:Python31
Self-driving-car-AI-using-deep-Q-learning
Language:Python1 1 00
Voice-controlled-trajectory-generation-and-control-of-a-hexarotor
Trajectory of the quad-rotor is generated by voice commands, which makes the control easier and the Quadrotor_Controller controls the drone's velocity, acceleration and pose.
Language:Python10

Nikhil619's Repositories

Nikhil619/Hybrid-Artificial-Potential-Fields-Algorithm-for-hexarotor
Language:Python3 1 00
Nikhil619/Human-following-hexa-rotor-with-obstacle-avoidance-using-YoloV3-and-StereoVision
Language:Python1 1 0
Nikhil619/Navigation-of-an-autonomous-rover-in-an-unknown-environment-by-localization-and-mapping
Language:Jupyter Notebook11
Nikhil619/Autonomous_Mobile_Robot
Autonomous mobile robot navigation using ROS Navigation Stack.
Nikhil619/ball_shooter
Language:Python1 0
Nikhil619/box_boy
Language:Python
Nikhil619/ComputerVision
Language:Jupyter Notebook
Nikhil619/cvpr2019_Pyramid-Feature-Attention-Network-for-Saliency-detection
code and model of Pyramid Feature Selective Network for Saliency detection
Nikhil619/Face
I have published my face related codes in this repository
Nikhil619/FaceIDLight
A lightweight face-recognition toolbox and pipeline based on tensorflow-lite
Nikhil619/frontier_exploration-1
ROS Node and Costmap 2D plugin layer for frontier exploration
Nikhil619/installROS
Install ROS Melodic on NVIDIA Jetson Development Kits
Language:Shell0 0
Nikhil619/linorobot2
Autonomous mobile robots (2WD, 4WD, Mecanum Drive)
Nikhil619/mobile-aloha-images-against-velocities
Mobile ALOHA: Learning Bimanual Mobile Manipulation with Low-Cost Whole-Body Teleoperation
Language:Jupyter Notebook0 0
Nikhil619/mono_vo_python
Visual odometry using monocular camera sequence and OpenCV.
Language:Python0 0
Nikhil619/motoman
ROS-Industrial Motoman support (http://wiki.ros.org/motoman)
Language:C++0 0
Nikhil619/multi-object-tracker
Multi-object trackers in Python
Nikhil619/Nikhil619
1 0
Nikhil619/ODM
A command line toolkit to generate maps, point clouds, 3D models and DEMs from drone, balloon or kite images. 📷
Language:Python0 0
Nikhil619/Orthophoto_Maps
A mapping software that generate individual maps(orthophotos) from images of drone
Nikhil619/pytorch-deep-image-matting
Pytorch implementation of deep image matting
Nikhil619/Pytorch-UNet
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
Nikhil619/PyTorch-YOLOv3
Minimal PyTorch implementation of YOLOv3
Language:Python0 0
Nikhil619/Resnet-Extract-Image-Feature-Pytorch-Python
Extract image features. A script inspired by the blog post: https://becominghuman.ai/extract-a-feature-vector-for-any-image-with-pytorch-9717561d1d4c
Nikhil619/ROS-Autonomous-Driving-and-Path-Planning-SLAM-with-TurtleBot
Nikhil619/ros2_documentation
ROS 2 docs repository
Nikhil619/ros_autonomous_slam
ROS package which uses the Navigation Stack to autonomously explore an unknown environment with help of GMAPPING and constructs a map of the explored environment. Finally, a path planning algorithm from the Navigation stack is used in the newly generated map to reach the goal. The Gazebo simulator is used for the simulation of the Turtlebot3 Waffle Pi robot. Various algorithms have been integrated for Autonomously exploring the region and constructing the map with help of the 360-degree Lidar sensor. Different environments can be swapped within launch files to generate a map of the environment.
Nikhil619/rtabmap_ros
RTAB-Map's ROS package.
Nikhil619/stereoDepth
single and stereo calibration, disparity calculation.
Nikhil619/wild_visual_navigation
Wild Visual Navigation: A system for fast traversability learning via pre-trained models and online self-supervision