Problem

Cosmo Logistic(CL) E-Yantra Robotics Competition 2023-24 theme

The challenge in inter-planet logistics demands a sophisticated sorting system for packages within a space station warehouse. The task involves efficient navigation of a mobile robot, precise identification of packages on racks, and the coordinated manipulation of a robotic arm for accurate picking. The complexity arises from the need to autonomously manage these tasks in a simulated environment (Gazebo) and later transition to a real-world setting in a warehouse at remote industry.

Solution (Git hub link)

To address this, we used technologies such as Robot Operating System 2 (ROS 2), Gazebo, MoveIt 2, Computer Vision, Git, RViz 2, and Nav 2. The integration of these tools will enable the development of an algorithm that facilitates the autonomous sorting of packages. The collaboration between a robotic arm and a mobile robot was orchestrated through sophisticated SLAM methods for efficient mapping and navigation within the warehouse.

Impact

The successful implementation of the "Cosmo Logistic" theme has far-reaching implications for space logistics. The ability to autonomously sort and prepare packages for inter-planetary transportation streamlines the workflow, reduces the risk of human error, and enhances the overall efficiency of logistics operations in a space station. This project not only addresses the specific challenges of inter-planet logistics but also contributes to the broader field of robotics and automation.

"Scored a perfect score in task1 and task2 and a received 15th and 22nd ranks."

Tasks Learned

ROS 2: Teams will gain expertise in working with Robot Operating System 2, a crucial framework for developing robotic software.
Gazebo: Simulation in Gazebo allows for the testing and refinement of algorithms in a controlled virtual environment before implementation in the real-world setting.
MoveIt 2: Learning to use MoveIt 2 facilitates motion planning for the robotic arm, ensuring accurate and efficient manipulation.
Computer Vision: Utilizing computer vision techniques enables the detection and localization of packages on racks, a fundamental aspect of the sorting process.
Git: Version control with Git ensures collaborative and organized development, enabling teams to track changes and manage code effectively.
RViz 2: RViz 2 aids in visualizing the robot's sensor data and state, providing essential insights for debugging and optimization.
Nav 2: Navigating the mobile robot using Nav 2 involves advanced algorithms for path planning and obstacle avoidance, crucial for efficient warehouse logistics.

Summery

The transition from a simulated environment to real hardware at IIT Bombay in the second stage of the competition further challenges teams to apply their algorithms in a practical, hands-on scenario, enhancing their problem-solving skills and adaptability. The comprehensive nature of this project ensures a holistic learning experience, covering theoretical concepts, simulation, and real-world application in the field of robotic inter-planet logistics.

Robotic Arm and Mobile Robot Improve Package Sorting