RoboCup@Home-Objects: Benchmarking Object Recognition for Home Robots

Massouh, Nizar; Brigato, Lorenzo; Iocchi, Luca

doi:10.1007/978-3-030-35699-6_31

Cited by 3 publications

(2 citation statements)

References 9 publications

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“…However, the data set for RoboCup@Home use is limited. Massouh et al (149) proposed a benchmark for object recognition, including a large-scale training set of 196,000 images labeled with classes derived from RoboCup@Home rule books (the RoboCup@Home-Objects data), two medium-scale test sets (one taken with a Pepper robot) with different objects and different backgrounds with respect to the training set, a robot behavior for image acquisition, and several useful analyses of the results. The RoboCup@Home-Objects data are very useful, not only for the teams participating in RoboCupSoccer but also for the technical committee designing and evaluating the competition.…”

Section: Performance Checkmentioning

confidence: 99%

Scientific and Technological Challenges in RoboCup

Asada

Stryk

2020

Annu. Rev. Control Robot. Auton. Syst.

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Since its inception in 1997, RoboCup has developed into a truly unique and long-standing research community advancing robotics and artificial intelligence through various challenges, benchmarks, and test fields. The main purposes of this article are to evaluate the research and development achievements so far and to identify new challenges and related new research issues. Unlike other robot competitions and research conferences, RoboCup eliminates the boundaries between pure research activities and the development of full system designs with hardware and software implementations at a site open to the public. It also creates specific scientific and technological research and development challenges to be addressed. In this article, we provide an overview of RoboCup, including its league structure and related research issues. We also review recent studies across several research categories to show how participants (called RoboCuppers) address the research and development challenges before, during, and after the annual competitions. Among the diversity of research issues, we highlight two unique aspects of the challenges: the platform design of the robots and the game evaluations. Both of these aspects contribute to solving the research and development challenges of RoboCup and verifying the results from a common perspective (i.e., a more objective view). Finally, we provide concluding remarks and discuss future research directions.

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Section: Performance Checkmentioning

confidence: 99%

Scientific and Technological Challenges in RoboCup

Asada

Stryk

2020

Annu. Rev. Control Robot. Auton. Syst.

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“…Even though the tasks referred fit the domestic environment standards, these can straightforwardly be adapted to healthcare purposes and environments due to their genericness. Regarding cognition, RoboCup@Home teams are already using machine learning technique primarily based on supervised learning to solve tasks such as face recognition [28], body pose estimation [29,30] and object detection [31,32].…”

Section: Introductionmentioning

confidence: 99%

CHARMIE: A Collaborative Healthcare and Home Service and Assistant Robot for Elderly Care

et al. 2021

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The global population is ageing at an unprecedented rate. With changes in life expectancy across the world, three major issues arise: an increasing proportion of senior citizens; cognitive and physical problems progressively affecting the elderly; and a growing number of single-person households. The available data proves the ever-increasing necessity for efficient elderly care solutions such as healthcare service and assistive robots. Additionally, such robotic solutions provide safe healthcare assistance in public health emergencies such as the SARS-CoV-2 virus (COVID-19). CHARMIE is an anthropomorphic collaborative healthcare and domestic assistant robot capable of performing generic service tasks in non-standardised healthcare and domestic environment settings. The combination of its hardware and software solutions demonstrates map building and self-localisation, safe navigation through dynamic obstacle detection and avoidance, different human-robot interaction systems, speech and hearing, pose/gesture estimation and household object manipulation. Moreover, CHARMIE performs end-to-end chores in nursing homes, domestic houses, and healthcare facilities. Some examples of these chores are to help users transport items, fall detection, tidying up rooms, user following, and set up a table. The robot can perform a wide range of chores, either independently or collaboratively. CHARMIE provides a generic robotic solution such that older people can live longer, more independent, and healthier lives.

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Analysis of Existing Datasets of Household Objects for AI-Enabled Techniques

Bhayana

Verma

2023

Lecture Notes in Networks and Systems

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RoboCup@Home-Objects: Benchmarking Object Recognition for Home Robots

Cited by 3 publications

References 9 publications

Scientific and Technological Challenges in RoboCup

Scientific and Technological Challenges in RoboCup

CHARMIE: A Collaborative Healthcare and Home Service and Assistant Robot for Elderly Care

Analysis of Existing Datasets of Household Objects for AI-Enabled Techniques

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