RoboCup@Home: Scientific Competition and Benchmarking for Domestic Service Robots

By Thomas Wisspeintner, T. V. D. Zant, Luca Iocchi, S. Schiffer. 2009

159 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Control and Systems Engineering, Mechanical Engineering

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Niko Sünderhauf
2. Peter Corke
3. Lei Tai
4. Lachlan Nicholson
5. Stephen James
6. Ben Upcroft
7. David Rovick Arrojo
8. Zicong Ma

In Control and Systems Engineering

1. Andrew J. Davison
2. Jürgen Leitner
3. Peter Corke
4. Stephen James
5. David Rovick Arrojo
6. Zicong Ma
7. Joseph W. Durham
8. Fangyi Zhang

In Mechanical Engineering

1. Peter Corke
2. Andrew J. Davison
3. Stephen James
4. Joseph W. Durham
5. Jürgen Leitner

Citations in the corpus

• RLBench: The Robot Learning Benchmark & Learning Environment (2019, background): “Similarly to ARC, the RoboCup@Home competition [29] is run annually, but has a greater range of tasks that must be completed.”
• Simitate: A Hybrid Imitation Learning Benchmark (2019, neutral): “In form of competitions like RoboCup@Home [42] robotic systems are benchmarked in domestic environments, however, due to the biannual changes of the rules and not fully objective opinions of referees the comparison should be seen critical.”
• The ACRV picking benchmark: A robotic shelf picking benchmark to foster reproducible research (2016, background): “The RoboCup@Home [17] competitions, for example, are held annually and cover a wide area of robotic system technologies with a focus on domestic use robots.”