ANKUR KOHLI's Projects
Solving Lunar Lander Problem using A2C & PPO algorithms in Reinforcement Learning.
The project simulates a hoist with 2 degrees of freedom, with two consoles that allow the user to interact with the hoist. The hoist can move right/left (horizontally) and up/down (vertically), within respective limits in axis.
This project is a set of 2 concurrent programs whose aim is to measure the speed of data transferring between a producer and a consumer using 2 different IPC transfer primitives, evaluating then their efficiency.
The dining philosophers problem which is used to demonstrate the concept of deadlock.
Config files for my GitHub profile.
The work is based on AI Planning which involves the demonstration of an automated warehouse for a company. An automated warehouse helps in order management in a precise way which automatically boost the storage capacity.
The work is based on Task and Motion Planning which involves the demon- stration of a coffee shop. This deals with the movement of a mobile robot in a constrained environment.
The exercises includes Image Filtering, Fourier Transformation, NCC-based Segmentation & Harris Corner Detection
The work is based on Embedded Systems which involves the implementation of timers, interrupts, SPI, UART, and so on. This assignment deals with MPLAB IDE Software, XC16 Compiler, HTerm serial software and Microchip Microcontroller Board.
The work is based on Embedded Systems which involves the implementation of timers, interrupts, SPI, UART, parser, ADC, PWM, Scheduling, and so on. This assignment deals with MPLAB IDE Software, XC16 Compiler, HTerm serial software and Microchip Microcontroller Board.
This project aims to develop an adaptive autonomous surveillance robot designed for indoor environments, incorporating advanced energy management systems to enhance operational efficiency and autonomy.
The second assignment integrates an autonomous surveillance robot into a simulated indoor environment for mapping and patrolling, showcasing its ability to build a semantic map, navigate autonomously, and conduct room scans.
To create immersive virtual reality experiences of robotics by capturing and converting real-world objects or environments into detailed 3D models.
Python script for achieving this robot’s behaviour such as constrantly drive the robot around the circuit in the counter-clockwise direction, avoid touching the golden boxes, and when the robot is close to a silver box, it should grab it, and move it behind itself
This is the second assignemnt of the Research Track 1. ROS(Robot Operating System) has been used to control the robot in the environment.
This is the third Assignment of the Research Track 1 in which an architecture is developed on ROS and its software capable of controlling a mobile robot in given enviroment along with creating a multiple modes for the user in which user allow to choose how to control the robot.
Sphinx is a documentation generator written and used by the Python community. It is written in Python, and also used in other environments.
Jupyter GUI to interact with the simulation of Software Architecture for Mobile Robot Control.
Statistical Analysis of the Python Robotics Simulator.
ROS-LLM is a framework designed for embodied intelligence applications in ROS. It allows natural language interactions and leverages Large Language Models (LLMs) for decision-making and robot control. With an easy configuration process, this framework allows for swift integration, enabling your robot to operate with it in as little as ten minutes.
ROS packages for ROSbot 2, 2R and 2 PRO
The work is based on Ontology which involves the topic in Ambient Intelligence (AmI). This will deals with Ambient Intelligence application.
This work is about the implementation of Keepout Zone using NAV2 packages. Also, this is implemented on ROS2, NAV2, Webots world, and so on.
Webots ROS 2 packages
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent