Lab

This laboratory is dedicated to advancing the capabilities of robot agents in seamlessly executing object transportation tasks within human-centric environments such as homes and retail spaces. It provides a versatile platform for exploring and refining generalized robot plans that manage the movement of diverse objects across varied settings for multiple purposes. By focusing on the adaptability and scalability of robotic programming, the lab aims to enhance the understanding and application of robotics in everyday contexts ultimately improving their generalizability, transferability, and effectiveness in real-world scenarios.

In the laboratory, you are equipped with a generalized open-source robotic plan capable of executing various object transportation-related tasks, including both table setting and cleaning, across diverse domestic settings. These settings range from entire apartments to kitchen environments and the plan is adaptable to various robots. You can customize the execution by selecting the appropriate environment, task, and robot, and then run it within a software container.

Happy New Year!

Wishing you an amazing 2025 filled with success, joy, and exciting opportunities.

My team and I would love for you to celebrate with us in our Virtual Research Building and help expand our robot community. And for the robots working in your labs, we look forward to seeing them join the party next year!

Here is to a successful and healthy 2025 together!

Best wishes,

Michael & Team Click: Opening Party Lab

openEASE is a cutting-edge, web-based knowledge service that leverages the KnowRob robot knowledge representation and reasoning system to offer a machine-understandable and processable platform for sharing knowledge and reasoning capabilities. It encompasses a broad spectrum of knowledge, including insights into agents (notably robots and humans), their environments (spanning objects and substances), tasks, actions, and detailed manipulation episodes involving both robots and humans. These episodes are richly documented through robot-captured images, sensor data streams, and full-body poses, providing a comprehensive understanding of interactions. OpenEASE is equipped with a robust query language and advanced inference tools, enabling users to conduct semantic queries and reason about the data to extract specific information. This functionality allows robots to articulate insights about their actions, motivations, methodologies, outcomes, and observations, thereby facilitating a deeper understanding of robotic operations and interactions within their environments.

In this laboratory, you have access to openEASE, a web-based interactive platform that offers knowledge services. Through openEASE, you can choose from various knowledge bases, each representing a robotic experiment or an episode where humans demonstrate tasks to robots. To start, select a knowledge base—for instance, ”ease-2020-urobosim-fetch-and-place”—and activate it. Then, by clicking on the ”examples” button, you can choose specific knowledge queries to run on the selected experiment’s knowledge bases, facilitating a deeper understanding and interaction with the data. For a detailed overview of the episodes in openEASE click here.