ΑΙhub.org
 

#RoboCup2019 @Home finals


by
08 July 2019



share this:


For the final stage of the @Home competition, the top 2 teams were selected in each of the sub-leagues (domestic, social and open platforms) to perform demos inside a 10 minute window followed by 5 minutes of questions from the judges. The scoring judges were comprised by trustee board members, external judges and members of the technical and organizing committees.

Social Standard Platform League
Uchile (2nd place) and UTS (1st place)

Chile showed an episodic memory demo based on their ongoing research, while UTS showed pepper as a social robot interacting with the “owner of the house” navigating environments and searching the house for the owner’s daughter.

Domestic Standard Platform League
Tidyboy (2nd place) and TUe (1st place)

Tidyboy did a demo about a manipulation task where the robot opened a cabinet door to get a juice, and then a snack from the kitchen table. It then placed both in a wheeled cart that it grabbed and took to the livingroom for a house guest.

TUe first showed how the robot understands pointing at objects in the room related to their research on human behavior recognition. Afterwards, they did a party demo where the robot recognized people in the livingroom and interfaced with a periscope app on a phone to get people’s drink orders. The robot then proceeded to navigate to the fridge, pushing a cart, to bring back multiple drinks at once and asked help from a bartender to get drinks from the fridge

Open Platform League
Pumas (2nd place) and Homer (1st place)

Pumas’ demo included both their robots from OPL and DSPL and showed how the robots can collaborate with tasks using cloud services like Alexa in social tasks like the robot party host.

As part of Homer’s final demo, they showed links to their ongoing research using their two open-platform robots about autonomous mapping, and adaptive learning from demonstration. As their last task of the demo they showcased the robot cleaning the toilet as part of a manipulation task that involves the use of contact forces.



tags:


Maru Cabrera is Research Associate at University of Washington.
Maru Cabrera is Research Associate at University of Washington.

            AUAI is supported by:



Subscribe to AIhub newsletter on substack



Related posts :

A faster way to estimate AI power consumption

  19 May 2026
The “EnergAIzer” method generates reliable results in seconds, enabling data center operators to efficiently allocate resources and reduce wasted energy.

Introducing ARFBench: A time series question-answering benchmark based on real incidents

  18 May 2026
To resolve system failures, engineers must troubleshoot outages quickly.

Does ‘federated unlearning’ in AI improve data privacy, or create a new cybersecurity risk?

  15 May 2026
As the capacity of AI systems increases apace, so do concerns about the privacy of user data.

Reflections from #AIES2025

and   14 May 2026
We reflect on AIES 2025, outlining a discussion session on LLMs for clinical usage and human rights.

Deep learning-powered biochip to detect genetic markers

System can detect extremely small amounts of microRNAs, genetic markers linked to diseases such as heart disease.

Half of AI health answers are wrong even though they sound convincing – new study

  12 May 2026
Imagine you have just been diagnosed with early-stage cancer and, before your next appointment, you type a question into an AI chatbot.

Gradient-based planning for world models at longer horizons

  11 May 2026
What were the problems that motivated this project and what was the approach to address them?

It’s tempting to offload your thinking to AI. Cognitive science shows why that’s a bad idea

  08 May 2026
Increased offloading to new tools has raised the fear that people will become overly reliant on AI.



AUAI is supported by:







Subscribe to AIhub newsletter on substack




 















©2026.02 - Association for the Understanding of Artificial Intelligence