Walking Together: Side by Side Walking Model for an Interacting Robot

Morales, Yoichi; Kanda, Takayuki; Hagita, Norihiro

doi:10.5898/jhri.3.2.morales

Cited by 45 publications

(30 citation statements)

References 32 publications

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“…destination unknown, for HRI [114]. All these work in 2014 [110,114] again confirm that people's walking behaviour people's walking behaviour, gaze models and human-like gaze behaviours are important for long-term modelling the HRI (see Table 4 for more details).…”

Section: Assessment Methodologies That Have Been Carried Out To Assesmentioning

confidence: 71%

“…In the same vein to support this research, in this year, i.e. 2014, Morales et al constructed a walking together -side by side walking model for an interacting robot [110], and Murakami et al created a framework for walking side-by-side without knowing the goal, i.e. destination unknown, for HRI [114].…”

Section: Assessment Methodologies That Have Been Carried Out To Assesmentioning

confidence: 98%

“…Crocker [157] 2011 [157] Mora et al [109] 2012 [117] Sakai et al [140] 2013 [109] Pateraki et al [126] 2013 [140] Murakami et al [114] 2014 [110] Morales et al [110] 2014 [114] 2014 [126] Hall [50] Psychological Model and Therapeutic Model (for research, therapy and entertainment) -based on Proximity Theory in Psychology, and/or related theories or principles…”

Section: Staudte Andmentioning

confidence: 99%

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Extensive assessment and evaluation methodologies on assistive social robots for modelling human–robot interaction – A review

Sim

Loo

2015

Information Sciences

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a b s t r a c tAssessment and evaluation methodologies as well as combinations of them, for modelling of Human-Robot Interaction (HRI), are reviewed extensively and thoroughly in this paper. However, based on the types of robots and the kinds of interactions involved in the modelling of HRI, we concentrate just on the assistive social robot types. A comprehensive review has been done on each of these extensive evaluation and assessment methodologies applied for testing the usability of assistive social robots, user acceptance towards robots and robot acceptance in terms of behavioural adaptation during the HRI. The evaluation methodologies are reviewed based on the primary and non-primary basis, while the assessment methodologies are reviewed based on the type(s) of modelling approaches. We then discussed the weaknesses, strengths and uniqueness of each type of the past research work done on the evaluation and assessment methodologies. Comparison and contrast tables are also illustrated. Lastly, this paper provides our recommended directions, new vision, as well as our inspirations and new insights for future researches by highlighting the key areas for enhancing each of the past evaluation and assessment methodologies so that a better modelling approach for HRI can be achieved. Contributions of this review paper are also discussed thoroughly.

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Section: Assessment Methodologies That Have Been Carried Out To Assesmentioning

confidence: 71%

Section: Assessment Methodologies That Have Been Carried Out To Assesmentioning

confidence: 98%

Section: Staudte Andmentioning

confidence: 99%

See 1 more Smart Citation

Extensive assessment and evaluation methodologies on assistive social robots for modelling human–robot interaction – A review

Sim

Loo

2015

Information Sciences

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“…Human-Robot Collaborative Navigation One of the first faced humanrobot collaborative challenges was side-by-side navigation [18,19]. In parallel, [8,9,11] approached this challenge through Social Force Model (SFM) methods and, in another context, [23,16] presented methods for side-by-side wheelchair navigation.…”

Section: Human-robot Collaborationmentioning

confidence: 99%

Human-Robot Collaborative Navigation Search Using Social Reward Sources

Dalmasso

Garrell

Jiménez

et al. 2019

Advances in Intelligent Systems and Computing

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This paper proposes a Social Reward Sources (SRS) design for a Human-Robot Collaborative Navigation (HRCN) task: humanrobot collaborative search. It is a flexible approach capable of handling the collaborative task, human-robot interaction and environment restrictions, all integrated on a common environment. We modelled task rewards based on unexplored area observability and isolation and evaluated the model through different levels of human-robot communication. The models are validated through quantitative evaluation against both agents' individual performance and qualitative surveying of participants' perception. After that, the three proposed communication levels are compared against each other using the previous metrics.

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“…They finally conclude that the leader-follower approach incorporates more advantages than the other. Morales et al [13], [14] proposed a model which describes people walking side-by-side and used this model to predict the future next position of the partner and to plan the next robot position. In our approach, we also predict the future next position, but we also look for the best path to not bother the human group trajectories and do the best path in the minimum time, moreover, we take into account the dynamic narrow passageways.…”

Section: Related Workmentioning

confidence: 99%

On-line adaptive side-by-side human robot companion in dynamic urban environments

Repiso

Ferrer

Sanfeliu

2017

2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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This paper presents an adaptive side-by-side human-robot companion approach for navigation in urban dynamic environments, based on the anticipative kinodynamic planning. The adaptive means that the robot is capable of adjusting its motion to the behavior of the person being accompanied. Our main objective is to optimize in real time the path performed by the pair human-robot, by modifying dynamically the angle and distance between both throughout different locations of the path. We have defined a new cost function for finding the best planned path that takes into account the cost of the geometrical configuration between the human and the robot. Moreover, we have modified the Extended Social Force Model (SFM) to include the required forces to maintain the angle and distance between the robot and human while the human-robot pair is moving towards the shared goal. The method has been validated throughout a large set of simulations and real-live experiments.

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Walking Together: Side by Side Walking Model for an Interacting Robot

Cited by 45 publications

References 32 publications

Extensive assessment and evaluation methodologies on assistive social robots for modelling human–robot interaction – A review

Extensive assessment and evaluation methodologies on assistive social robots for modelling human–robot interaction – A review

Human-Robot Collaborative Navigation Search Using Social Reward Sources

On-line adaptive side-by-side human robot companion in dynamic urban environments

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