Scene Perception and Recognition in Industrial Environments for Human-Robot Interaction

Somani, Nikhil; Dean-León, Emmanuel; Cai, Caixia; Knoll, Alois

doi:10.1007/978-3-642-41914-0_37

Cited by 5 publications

(1 citation statement)

References 21 publications

(25 reference statements)

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“…The authors categorize different approaches according to the mapping between the teacher and the learner. Teleoperation is used to learn the grasping of objects [21] or to perform tasks demonstrated by kinesthetic teaching [22]. If the learner uses its own sensors, but the teacher does not directly control the learner's platform, it is referred to as shadowing.…”

Section: Related Workmentioning

confidence: 99%

A framework for interactive teaching of virtual borders to mobile robots

Sprute

Rasch

Tönnies

et al. 2017

2017 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN)

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The increasing number of robots in home environments leads to an emerging coexistence between humans and robots. Robots undertake common tasks and support the residents in their everyday life. People appreciate the presence of robots in their environment as long as they keep the control over them. One important aspect is the control of a robot's workspace. Therefore, we introduce virtual borders to precisely and flexibly define the workspace of mobile robots. First, we propose a novel framework that allows a person to interactively restrict a mobile robot's workspace. To show the validity of this framework, a concrete implementation based on visual markers is implemented. Afterwards, the mobile robot is capable of performing its tasks while respecting the new virtual borders. The approach is accurate, flexible and less time consuming than explicit robot programming. Hence, even non-experts are able to teach virtual borders to their robots which is especially interesting in domains like vacuuming or service robots in home environments.

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Section: Related Workmentioning

confidence: 99%

A framework for interactive teaching of virtual borders to mobile robots

Sprute

Rasch

Tönnies

et al. 2017

2017 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN)

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Object Recognition Using Constraints from Primitive Shape Matching

Somani¹,

Cai

Perzylo³

et al. 2014

Advances in Visual Computing

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Scene Perception and Recognition for Human-Robot Co-operation

Somani

Dean-León

Cai

et al. 2013

New Trends in Image Analysis and Processing – ICIAP 2013

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Abstract. In this paper, a combination of perception modules and reasoning engines is used for scene understanding in typical Human-Robot Interaction(HRI) scenarios. The major contribution of this work lies in a 3D object detection, recognition and pose estimation module, which can be trained using CAD models and works for noisy data, partial views and in cluttered scenes. This perception module is combined with first-order logic reasoning to provide a semantic description of scenes, which is used for process planning. This abstraction of the scene is an important concept in the design of intelligent robotic systems which can adapt to unstructured and rapidly changing environments since it provides a separation of the process planning problem from its execution and scenario-specific parameters. This work is aimed at HRI applications in industrial settings and has been evaluated in several experiments and demonstration scenarios for autonomous process plan execution, humanrobot interaction and co-operation.

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Scene Perception and Recognition in Industrial Environments for Human-Robot Interaction

Cited by 5 publications

References 21 publications

A framework for interactive teaching of virtual borders to mobile robots

A framework for interactive teaching of virtual borders to mobile robots

Object Recognition Using Constraints from Primitive Shape Matching

Scene Perception and Recognition for Human-Robot Co-operation

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