Authors
- Alessandra Rossi*
- Maike Paetzel-Prüsmann*
- Merel Keijsers*
- Michael Anderson*
- Susan Leigh Anderson*
- Daniel Barry*
- Jan Gutsche*
- Justin Hart*
- Luca Iocchi*
- Ainse Kokkelmans*
- Wouter Kuijpers*
- Yun Liu*
- Daniel Polani*
- Caleb Roscon*
- Marcus Scheunemann*
- Peter Stone
- Florian Vahl*
- René van de Molengraft*
- Oskar von Stryk*
* External authors
Venue
- AR-24
Date
- 2024
Share
The Human in the Loop: Perspectives and Challenges for RoboCup 2050.
Alessandra Rossi*
Maike Paetzel-Prüsmann*
Merel Keijsers*
Michael Anderson*
Susan Leigh Anderson*
Daniel Barry*
Jan Gutsche*
Justin Hart*
Luca Iocchi*
Ainse Kokkelmans*
Wouter Kuijpers*
Yun Liu*
Daniel Polani*
Caleb Roscon*
Marcus Scheunemann*
Florian Vahl*
René van de Molengraft*
Oskar von Stryk*
* External authors
AR-24
2024
Abstract
Robotics researchers have been focusing on developing autonomous and human-like intelligent robots that are able to plan, navigate, manipulate objects, and interact with humans in both static and dynamic environments. These capabilities, however, are usually developed for direct interactions with people in controlled environments, and evaluated primarily in terms of human safety. Consequently, human-robot interaction (HRI) in scenarios with no intervention of technical personnel is under-explored. However, in the future, robots will be deployed in unstructured and unsupervised environments where they will be expected to work unsupervised on tasks which require direct interaction with humans and may not necessarily be collaborative. Developing such robots requires comparing the effectiveness and efficiency of similar design approaches and techniques. Yet, issues regarding the reproducibility of results, comparing different approaches between research groups, and creating challenging milestones to measure performance and development over time make this difficult. Here we discuss the international robotics competition called RoboCup as a benchmark for the progress and open challenges in AI and robotics development. The long term goal of RoboCup is developing a robot soccer team that can win against the world’s best human soccer team by 2050. We selected RoboCup because it requires robots to be able to play with and against humans in unstructured environments, such as uneven fields and natural lighting conditions, and it challenges the known accepted dynamics in HRI. Considering the current state of robotics technology, RoboCup’s goal opens up several open research questions to be addressed by roboticists. In this paper, we (a) summarise the current challenges in robotics by using RoboCup development as an evaluation metric, (b) discuss the state-of-the-art approaches to these challenges and how they currently apply to RoboCup, and (c) present a path for future development in the given areas to meet RoboCup’s goal of having robots play soccer against and with humans by 2050.
Related Publications
Having explored an environment, intelligent agents should be able to transfer their knowledge to most downstream tasks within that environment. Referred to as ``zero-shot learning," this ability remains elusive for general-purpose reinforcement learning algorithms. While rec…
Scaling up the model size and computation has brought consistent performance improvements in supervised learning. However, this lesson often fails to apply to reinforcement learning (RL) because training the model on non-stationary data easily leads to overfitting and unstab…
Deep reinforcement learning has achieved superhuman racing performance in high-fidelity simulators like Gran Turismo 7 (GT7). It typically utilizes global features that require instrumentation external to a car, such as precise localization of agents and opponents, limiting …
JOIN US
Shape the Future of AI with Sony AI
We want to hear from those of you who have a strong desire
to shape the future of AI.
