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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.
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The Role of Physics-Based Simulators in Robotics
Physics-based simulation provides an accelerated and safe avenue for developing, verifying, and testing robotic control algorithms and prototype designs. In the quest to leverage machine learning for developing AI-enabled robots, physics-based simulation can generate a wealth of labeled training data in a short amount of time. Physics-based simulation also creates an ideal proving ground for developing intelligent robots that can both learn from their mistakes and be verifiable. This article provides an overview of the use of simulation in robotics, emphasizing how robots (with sensing and actuation components), the environment they operate in, and the humans they interact with are simulated in practice. It concludes with an overview of existing tools for simulation in robotics and a short discussion of aspects that limit the role that simulation plays today in intelligent robot design.
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- Award ID(s):
- 1739869
- PAR ID:
- 10276894
- Date Published:
- Journal Name:
- Annual Review of Control, Robotics, and Autonomous Systems
- Volume:
- 4
- Issue:
- 1
- ISSN:
- 2573-5144
- Page Range / eLocation ID:
- 35 to 58
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1146/annurev-control-072220-093055
