Improving human-robot interactivity for tele-operated industrial and service robot applications

Wu, Yan; Chan, Wei Liang; Li, Yanan; Tee, Keng Peng; Yan, Rui; Limbu, Dilip Kumar

doi:10.1109/iccis.2015.7274565

Cited by 11 publications

(6 citation statements)

References 13 publications

(11 reference statements)

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“…Two main approaches are addressed in the literature: template-based (or prompts) and generative models [8]. Our current implementation allows mainly the usage of templates defined in the definition of the dialog states (see section D), although basic generation is also allowed by using the open-sourced toolkit SimpleNLG 1 .…”

Section: B Text-to-speech and Natural Language Generationmentioning

confidence: 99%

“…However, its integration with other components and modalities poses some requirements in terms of reliability, speed, flexibility and modularity. In this paper, we want to describe a scalable platform which allows different kind of industrial tasks to be performed (in our case, we have used to resemble a welding task, a gluing task and a drawing by example task [1] [2]). This way, for instance the operator can set the values of different parameters required for each task, e.g.…”

Section: Introductionmentioning

confidence: 99%

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An integrated framework for multimodal human-robot interaction

D’Haro

Niculescu

Cai³

et al. 2017

2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)

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Recent research progresses in speech recognition, text-to-speech, natural language understanding, or dialog management components are improving the way humans interact with advanced robot machines. However, far from being solved, we are just starting the process of creating meaningful multimodal platforms that can allow operators to use and control industrial robots through spoken dialogue.This paper describes our ongoing efforts on creating a modular platform that combines different technologies to cover typical requirements in an industrial setting, i.e. robust speech recognition, low level skill functions to operate the robot, recommendations and validation procedures to setup parameters, combination of audio-visual information for challenging environments, integration of domain-knowledge by means of an ontology, a flexible definition of the dialog model and natural language rules, as well as a test and control interface to quickly check the functionality of each module during development and operation. All platform modules are intercommunicated by the ROS operative system which allows the integration of external plugins and modules easily.Finally, a preliminary user study with IT experts simulating a welding task has been doing giving us clues on what should be the focus of our next developments.

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Section: B Text-to-speech and Natural Language Generationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An integrated framework for multimodal human-robot interaction

D’Haro

Niculescu

Cai³

et al. 2017

2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)

View full text Add to dashboard Cite

show abstract

“…Many researchers have used the master-slave control strategy in telerobotic applications. The application can be found in industry, such as the soldering process, pick and place, painting, screwing, and deburring [2], [3]. In 2018, a teleoperated robot system was improved and implemented through augmented reality (AR) to allow the operator to perform and program these manipulation tasks with better accuracy, dexterity, and visualization with minimal error [4].…”

Section: Introductionmentioning

confidence: 99%

Development of a low-cost teleoperated and semi-autonomous robotic arm

Yaacob

Jalani

Sadun

et al. 2022

IJEECS

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A safe human-robot physical interaction is required when the robot is used to help humans. This can be achieved by introducing a teleoperated robotic arm in which a human can teach the robot before performing tasks remotely. This paper develops and establishes a three-degree-of-freedom robotic arm and teaching pendant. In particular, a flexible robotic arm is operated in two different modes, namely, the teleoperated mode and the semi-autonomous mode. The teleoperated mode is a manual control using a teaching pendant, where the robot arm replicates various movements of the teaching pendant. On the contrary, the semi-autonomous mode allows the robot to execute a task from one point to another point repetitively after at least one training of the teaching pendant. The Arduino Uno board is employed as a microcontroller, and the integrated development environment ( IDE ) software is used to write and upload the computer code. A series of tests in which the robot performs different tasks is recorded to evaluate the accuracy and consistency of the semi-autonomous and teleoperated modes. The results show that the performance of the proposed low-cost teleoperated robotic arm is reliable and safe to perform various tasks based on the teaching pendant.

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“…Therefore, there is a great opportunity for industries to gain a competitive edge through the implementation of collaborative robotic systems able to interact with humans [13,14]. New and robust sensing capabilities are needed to provide robotic systems with reasoning and autonomous thinking [15,16], where these capabilities have to reliably perceive the robot workspace under real working conditions.…”

Section: Introductionmentioning

confidence: 99%

Smart Sensing and Adaptive Reasoning for Enabling Industrial Robots with Interactive Human-Robot Capabilities in Dynamic Environments—A Case Study

Zabalza

Fei

Wong

et al. 2019

Sensors

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Traditional industry is seeing an increasing demand for more autonomous and flexible manufacturing in unstructured settings, a shift away from the fixed, isolated workspaces where robots perform predefined actions repetitively. This work presents a case study in which a robotic manipulator, namely a KUKA KR90 R3100, is provided with smart sensing capabilities such as vision and adaptive reasoning for real-time collision avoidance and online path planning in dynamically-changing environments. A machine vision module based on low-cost cameras and color detection in the hue, saturation, value (HSV) space is developed to make the robot aware of its changing environment. Therefore, this vision allows the detection and localization of a randomly moving obstacle. Path correction to avoid collision avoidance for such obstacles with robotic manipulator is achieved by exploiting an adaptive path planning module along with a dedicated robot control module, where the three modules run simultaneously. These sensing/smart capabilities allow the smooth interactions between the robot and its dynamic environment, where the robot needs to react to dynamic changes through autonomous thinking and reasoning with the reaction times below the average human reaction time. The experimental results demonstrate that effective human-robot and robot-robot interactions can be realized through the innovative integration of emerging sensing techniques, efficient planning algorithms and systematic designs.

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Improving human-robot interactivity for tele-operated industrial and service robot applications

Cited by 11 publications

References 13 publications

An integrated framework for multimodal human-robot interaction

An integrated framework for multimodal human-robot interaction

Development of a low-cost teleoperated and semi-autonomous robotic arm

Smart Sensing and Adaptive Reasoning for Enabling Industrial Robots with Interactive Human-Robot Capabilities in Dynamic Environments—A Case Study

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