On Planning and Task Achievement Modalities for Human-Robot Collaboration

Fiore, Michelangelo; Clodic, Aurélie; Alami, Rachid

doi:10.1007/978-3-319-23778-7_20

Cited by 32 publications

(29 citation statements)

References 27 publications

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“…about planning failures or potential dangers for humans, and reacts accordingly. Using the work of Fiore et al (2014), the SUP was built and sucessfully tested in a simplified scenario.…”

Section: The Supervision Systemmentioning

confidence: 99%

SPENCER: A Socially Aware Service Robot for Passenger Guidance and Help in Busy Airports

Triebel

Arras

Alami

et al. 2016

Springer Tracts in Advanced Robotics

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195

120

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We present an ample description of a socially compliant mobile robotic platform, which is developed in the EU-funded project SPENCER. The purpose of this robot is to assist, inform and guide passengers in large and busy airports. One particular aim is to bring travellers of connecting flights conveniently and efficiently from their arrival gate to the passport control. The uniqueness of the project stems from the strong demand of service robots for this application with a large potential impact for the aviation industry on one side, and on the other side from the scientific advancements in social robotics, brought forward and achieved in SPENCER. The main contributions of SPENCER are novel methods to perceive, learn, and model human social behavior and to use this knowledge to plan appropriate actions in realtime for mobile platforms. In this paper, we describe how the project advances the fields of detection and tracking of individuals and groups, recognition of human social relations and activities, normative human behavior learning, socially-aware task and motion planning, learning socially annotated maps, and conducting empirical experiments to assess socio-psychological effects of normative robot behaviors.

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“…about planning failures or potential dangers for humans, and reacts accordingly. Using the work of Fiore et al (2014), the SUP was built and sucessfully tested in a simplified scenario.…”

Section: The Supervision Systemmentioning

confidence: 99%

SPENCER: A Socially Aware Service Robot for Passenger Guidance and Help in Busy Airports

Triebel

Arras

Alami

et al. 2016

Springer Tracts in Advanced Robotics

Self Cite

195

120

View full text Add to dashboard Cite

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“…Baraka and Veloso [2] define three user models to adapt the luminous interactions between a robot and the user over time, learning the model parameters from user feedback. Personalized collaboration is shown in Fiore et al [8], where an object manipulation task is performed jointly by the robot and the user whose preferences are taken into account. Abdo et al [1] predict user preferences to tidy up objects in containers using collaborative filtering based on crowdsourced data and the observations of current dispositions or by querying the user.…”

Section: Related Workmentioning

confidence: 99%

Personalization Framework for Adaptive Robotic Feeding Assistance

2016

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Abstract. The deployment of robots at home must involve robots with pre-defined skills and the capability of personalizing their behavior by non-expert users. A framework to tackle this personalization is presented and applied to an automatic feeding task. The personalization involves the caregiver providing several examples of feeding using Learning-byDemostration, and a ProMP formalism to compute an overall trajectory and the variance along the path. Experiments show the validity of the approach in generating different feeding motions to adapt to user's preferences, automatically extracting the relevant task parameters. The importance of the nature of the demonstrations is also assessed, and two training strategies are compared.

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“…In this system, the execution can be stopped and a new plan computed in case of unexpected situations. Fiore et al extended this work in a more robust way that includes new aspects of joint action like reactive action execution [21]. Fong et al present HRI/OS, a system able to produce and schedule tasks for different agents based on their capacities [22].…”

Section: Introductionmentioning

confidence: 99%

An implemented theory of mind to improve human-robot shared plans execution

Devin

Alami

2016

2016 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

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111

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When a robot has to execute a shared plan with a human, a number of unexpected situations and contingencies can happen due, essentially, to human initiative. For instance, a temporary absence or inattention of the human can entail a partial, and potentially not sufficient, knowledge about the current situation. To ensure a successful and fluent execution of the shared plan the robot might need to detect such situations and be able to provide the information to its human partner about what he missed without being annoying or intrusive. To do so, we have developed a framework which allows a robot to estimate the other agents mental states not only about the environment but also about the state of goals, plans and actions and to take them into account when executing human-robot shared plans.

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On Planning and Task Achievement Modalities for Human-Robot Collaboration

Cited by 32 publications

References 27 publications

SPENCER: A Socially Aware Service Robot for Passenger Guidance and Help in Busy Airports

SPENCER: A Socially Aware Service Robot for Passenger Guidance and Help in Busy Airports

Personalization Framework for Adaptive Robotic Feeding Assistance

An implemented theory of mind to improve human-robot shared plans execution

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