For Entering Chapter four click here: Chapter 4!
Welcome to the fourth day of our hands-on course!
Today, you will focus on executing the complete task of transporting milk from the fridge to the table. This session will integrate all the knowledge and skills you've developed so far.Goal: By the end of the session, you will have successfully completed the full milk delivery task, demonstrating how to combine perception, planning, and knowledge retrieval.
Prerequisites
- Ensure you have completed Chapters 1-3 and have a solid understanding of URDF, perception, and planning.
Theoretical Background
- We will recap all components involved in the task: URDF, perception, planning, and knowledge base utilization.
- You will learn about common simulation gaps and limitations that may arise during task execution.
- Discover the concept of Multiverse and how various physical simulations can address distinct challenges.
Bullet World
The Bullet World in PyCRAM serves as a simulation environment based on the Bullet physics engine, allowing for detailed robotic task simulation. Here’s a breakdown to include in your tutorial:
What is Bullet World? Bullet World is a physics-based simulation space within PyCRAM, which provides essential physics support for simulating robots, objects, and interactions. It uses the Bullet physics engine to simulate aspects like collision detection, rigid body dynamics, and constraints, all of which are crucial for realistic robotic task planning and execution.
Key Features of Bullet World
Object Handling: Bullet World lets you spawn, move, and interact with objects in a 3D simulated space. Robots and objects are imported using URDF (Unified Robot Description Format) files, enabling detailed representations of their structure and properties.
Collision Detection: The environment includes built-in collision detection, allowing the robot to interact naturally with objects and other entities in the world. This feature is essential for tasks involving manipulation, grasping, and placing objects.
Environment Control: Bullet World provides commands to control the environment, like resetting positions, adding or removing objects, and stepping through the simulation. This control is useful for creating specific scenarios or repeating tasks for testing.
Multiverse
Multiverse is a simulation framework designed to integrate multiple advanced physics engines such as MuJoCo, Project Chrono, and SOFA along with various photo-realistic graphics engines like Unreal Engine and Omniverse. Additionally, Multiverse provides the capability to generate knowledge graphs dynamically during runtime.
Step-by-Step Hands-On Exercises
- Create a Task Plan: Develop a comprehensive plan that incorporates all previous learnings.
- Simulate the Full Task: Execute the task by opening the fridge, perceiving the milk, picking it up, and placing it on the table.
Interactive Actions and/or Examples
For Hands-On Exercises please use the following Virtual Lab: Plan Executive
Summary
By the end of this session, you will have a clear understanding of how to integrate various components to achieve complex robotic tasks.
Further Reading/Exercises
- Explore alternative strategies for task execution, including different object placements and adjustments to the environment.
- Discuss the differences between real-world gaps versus simulation limitations and how to manage them effectively.
Example Videos
Multiverse Overview:
