Human Motion Analysis and Simulation Tools

Nunes, João Ferreira; Moreira, Pedro Miguel; Tavares, João Manuel R. S.

doi:10.4018/978-1-4666-8823-0.ch012

Cited by 8 publications

(5 citation statements)

References 76 publications

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“…Human motion analysis has also made progress, leading to musculo-skeletal analysis allowing to estimate activities of hundreds of muscles ( Nakamura et al, 2005 ; Ayusawa and Nakamura, 2012 ), as well as some commercial products such as SIMM and AnyBody ( Nunes et al, 2015 ). Simulation tools with digital human models like Dhaiba ( Endo et al, 2014 ) and THUMS ( Iwamoto et al, 2002 ) integrate contact models to simulate products with the dynamic reaction of the human body.…”

Section: Challenges For Contact-rich Motions Through Icphmentioning

confidence: 99%

Towards understanding and synthesis of contact-rich anthropomorphic motions through interactive cyber-physical human

Yoshida

2022

Front. Robot. AI

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This article presents perspective on the research challenge of understanding and synthesizing anthropomorphic whole-body contact motions through a platform called “interactive cyber-physical human (iCPH)” for data collection and augmentation. The iCPH platform combines humanoid robots as “physical twins” of human and “digital twins” that simulates humans and robots in cyber-space. Several critical research topics are introduced to address this challenge by leveraging the advanced model-based analysis together with data-driven learning to exploit collected data from the integrated platform of iCPH. Definition of general description is identified as the first topic as a common basis of contact motions compatible to both humans and humanoids. Then, we set continual learning of a feasible contact motion network as the second challenge by benefiting from model-based approach and machine learning bridged by the efficient analytical gradient computation developed by the author and his collaborators. The final target is to establish a high-level symbolic system allowing automatic understanding and generation of contact motions in unexperienced environments. The proposed approaches are still under investigation, and the author expects that this article triggers discussions and further collaborations from different research communities, including robotics, artificial intelligence, neuroscience, and biomechanics.

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Section: Challenges For Contact-rich Motions Through Icphmentioning

confidence: 99%

Towards understanding and synthesis of contact-rich anthropomorphic motions through interactive cyber-physical human

Yoshida

2022

Front. Robot. AI

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“…This has led to the implementation of Red Green Blue-Depth (RGB-D) images, which define the RGB values and the distance between the RGB-D sensor of the camera and the captured object of interest. As mentioned in [ 42 , 43 ], depth information is obtained by stereovision [ 44 ], time of flight (TOF) [ 17 , 45 ], or structured light [ 46 ] depth cameras. The described types of depth cameras are shown in Figure 3 .…”

Section: Preliminariesmentioning

confidence: 99%

“…The described types of depth cameras are shown in Figure 3 . According to [ 42 , 43 ], the working principles of depth cameras can be shortly described as follows: Stereovision cameras use the triangulation principle for the calculation of the depth of a captured scene. The use of two or more image sensors or cameras is needed to perceive depth, simulating human binocular perception.…”

Section: Preliminariesmentioning

confidence: 99%

Vision and RTLS Safety Implementation in an Experimental Human—Robot Collaboration Scenario

Slovák

Melicher

Šimovec

et al. 2021

Sensors

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Human–robot collaboration is becoming ever more widespread in industry because of its adaptability. Conventional safety elements are used when converting a workplace into a collaborative one, although new technologies are becoming more widespread. This work proposes a safe robotic workplace that can adapt its operation and speed depending on the surrounding stimuli. The benefit lies in its use of promising technologies that combine safety and collaboration. Using a depth camera operating on the passive stereo principle, safety zones are created around the robotic workplace, while objects moving around the workplace are identified, including their distance from the robotic system. Passive stereo employs two colour streams that enable distance computation based on pixel shift. The colour stream is also used in the human identification process. Human identification is achieved using the Histogram of Oriented Gradients, pre-learned precisely for this purpose. The workplace also features autonomous trolleys for material supply. Unequivocal trolley identification is achieved using a real-time location system through tags placed on each trolley. The robotic workplace’s speed and the halting of its work depend on the positions of objects within safety zones. The entry of a trolley with an exception to a safety zone does not affect the workplace speed. This work simulates individual scenarios that may occur at a robotic workplace with an emphasis on compliance with safety measures. The novelty lies in the integration of a real-time location system into a vision-based safety system, which are not new technologies by themselves, but their interconnection to achieve exception handling in order to reduce downtimes in the collaborative robotic system is innovative.

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“…The analysis of human motions has been a very active research topic, with a manifold of potential applications. Some of them have already been discussed in reviews like [22,27,20,30]. Particularly, gait, as a specific type of human movement, has been used for a wide range of applications, either as a data source or simply as a way to interact with them.…”

Section: Introductionmentioning

confidence: 99%

Benchmark RGB-D Gait Datasets: A Systematic Review

2019

Self Cite

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Human motion analysis has proven to be a great source of information for a wide range of applications. Several approaches for a detailed and accurate motion analysis have been proposed in the literature, as well as an almost proportional number of dedicated datasets. The relatively recent arrival of depth sensors contributed to an increasing interest in this research area and also to the emergence of a new type of motion datasets. This work focuses on a systematic review of publicly available depth-based datasets, encompassing human gait data which is used for person recognition and/or classification purposes. We have conducted this systematic review using the Scopus database. The herein presented survey, which to the best of our knowledge is the first one dedicated to this type of datasets, is intended to inform and aid researchers on the selection of the most suitable datasets to develop, test and compare their algorithms.

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Human Motion Analysis and Simulation Tools

Abstract: Resumo

Cited by 8 publications

References 76 publications

Towards understanding and synthesis of contact-rich anthropomorphic motions through interactive cyber-physical human

Towards understanding and synthesis of contact-rich anthropomorphic motions through interactive cyber-physical human

Vision and RTLS Safety Implementation in an Experimental Human—Robot Collaboration Scenario

Benchmark RGB-D Gait Datasets: A Systematic Review

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