Tasks and Duties
This week, you will be tasked with setting up a virtual simulation environment tailored for robotics programming. The main objective is to build and configure a simulation platform (using publicly available tools such as Gazebo or Webots) that emulates a basic mobile robot. You will need to install the simulation tool, configure the environment with at least one mobile robot model, and write a simple control program that moves the robot along predefined paths. You are expected to create a well-documented project folder including a README file that explains the installation and setup process. Additionally, you will write a control script (using Python, C++, or another language of your choice) that demonstrates basic command execution and control of the simulated robot.
The task is designed to take approximately 30 to 35 hours of work and requires you to apply practical robotics programming and system configuration skills. In your submission, include the simulation setup files, the code for the control program, and a detailed report in PDF format documenting your setup process, challenges faced, and how you resolved them. Evaluation criteria include clarity of documentation, functionality of your code, completeness of the simulation setup, and adherence to task requirements. This task will test your ability to work independently on a virtual setup, and the final deliverable must be a single compressed file (.zip) containing all necessary files and documentation.
This week, your challenge focuses on the realm of robotic arm kinematics. You are required to design and program an algorithm for the forward and inverse kinematics of a simulated robotic arm. The objective is to accurately compute joint angles for desired positions in a virtual workspace and then validate the results through simulation. Start by researching concepts behind robotic arm kinematics, then create mathematical models, and finally implement these models in code using programming languages like Python or MATLAB.
Your deliverables should include a well-commented code file (or files) that performs kinematic calculations, a simulation file demonstrating the robotic arm's movement in response to your algorithms, and a comprehensive technical report. The report should explain your approach, include diagrams of the robotic arm, detail the mathematical derivations, and describe the testing process used to validate the model. Include screenshots or simulation outputs that prove the correctness of your implementation. Spend an estimated 30 to 35 hours on this task, ensuring that you highlight your technical reasoning and problem-solving methods. The final submission must be a compressed package of all code, simulation files, and the PDF report.
This week, you will delve into the design and simulation of a path planning and obstacle avoidance system for a mobile robot. The goal is to develop an algorithm that allows a robot to navigate from a starting point to an endpoint while avoiding obstacles in its path. You may choose to implement algorithms such as A*, Dijkstra, or RRT, and contextualize them within a simulated environment using tools like ROS combined with a simulation engine (e.g., Gazebo). The project should include both the algorithm implementation and the simulation demonstrating its efficacy.
The final deliverable for this task is a composite file upload containing a fully commented source code file, a simulation project file, and a detailed explanatory document. This report should include the rationale behind your algorithm selection, design choices, implementation methodology, and a discussion on the limitations and potential improvements. Expect this task to require 30 to 35 hours of work, during which you will have to iteratively test and refine your algorithm using a virtual environment. Your evaluation will be based on the performance of the algorithm in navigating around obstacles, the quality and robustness of your simulation setup, and the depth of your technical documentation. Please ensure your submission is a single zip file including all necessary content.
This assignment focuses on integrating simulated sensor data to enhance robotic perception. You are required to design and implement a module that integrates data from multiple sensors such as LIDAR, ultrasonic sensors, or cameras. The task involves the development of a data fusion algorithm that combines sensor inputs to create a reliable model of the robot’s surroundings in the virtual environment. Start by selecting at least two types of simulated sensors and integrating their data into your robotic system setup.
A successful submission will include the source code for sensor data processing and fusion, along with a simulation file that demonstrates real-time sensor data integration. Additionally, you must prepare a detailed report (PDF) describing your system architecture, the algorithms used for data fusion, and a discussion on the benefits and challenges associated with integrating heterogeneous sensor data. The report should contain diagrams illustrating sensor placement, the data flow, and steps taken to ensure accuracy and robustness in the simulation. This task is estimated to take approximately 30 to 35 hours and is designed to test both your programming and system integration skills. Your final submission should be a compressed file containing all code files, simulation configurations, and documentation.
This week’s task challenges you to develop and simulate an autonomous navigation system, with a strong emphasis on localization techniques. You will design an algorithm that uses methods like Kalman Filters, Particle Filters, or SLAM to determine the robot’s position within a predefined virtual environment. Your goal is to not only implement the localization algorithm but also integrate it with a navigation controller that allows the robot to autonomously traverse waypoints while dynamically updating its position.
The deliverables for this assignment include a complete source code package, simulation files that demonstrate the driving process, and a thorough technical report. The report should articulate the theory behind the chosen localization technique, steps for integration with the navigation system, and performance metrics derived from your simulation tests. Be sure to include graphs, charts, and screen captures that reflect the robot’s localization accuracy and path execution. This task is designed to require around 30 to 35 hours of carefully planned work, testing both your algorithmic and simulation skills. Your final submission must be a zip file that contains all the necessary scripts, simulation configurations, and the detailed PDF report.
The final week integrates the various components you have worked on into a cohesive robotic control system. Your task is to simulate a complete robotic system that integrates motion planning, sensor fusion, kinematics, and autonomous navigation. Beyond basic integration, the focus of this assignment is on how well the system handles unexpected faults and optimization challenges in the virtual environment. You will need to design scenarios in which the robot must adapt to sensor failures or obstacles and optimize its performance under varying simulated conditions.
Your submission should include all source codes used to develop the system, simulation project files demonstrating integrated functionality, and a comprehensive technical report. This report must detail the integration process, describe fault tolerance mechanisms implemented, and discuss optimization strategies used to enhance system performance. The evaluation criteria will include the robustness of your system under simulated failure conditions, clarity in the description of your integration strategy, and effectiveness in system performance optimization. Allocate about 30 to 35 hours to this multifaceted assignment. The final deliverable is a single compressed (.zip) file that includes all code, simulation setups, and a detailed PDF report outlining your design decisions, challenges encountered, and final outcomes.