Expressive states with a robot arm using adaptive fuzzy and robust predictive controllers

Rincon, Liz; Coronado, Enrique; Hendra, Hansen; Phan, Julyando; Zainalkefli, Zur; Venture, Gentiane

doi:10.1109/iccre.2018.8376425

Cited by 10 publications

(2 citation statements)

References 14 publications

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“…RIZE has been used for the remote control and the generation of intelligent behaviors using a ROS-based Turtlebot Burger robot, Nao and Pepper humanoid robots, as well as a robot manipulator built with Dynamixel servomotors and controlled in Matlab/Simulink. Real-world applications include museum exhibitions and theater performance [64] , child-robot interaction [126,127] , long-term human-robot interaction experiments in home settings and research in emotional intelligence for robots [128] . RIZE is available online [101] .…”

Section: Block-based Interfacesmentioning

confidence: 99%

Visual Programming Environments for End-User Development of intelligent and social robots, a systematic review

Coronado

Mastrogiovanni

Indurkhya

et al. 2020

Journal of Computer Languages

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Robots are becoming interactive and robust enough to be adopted outside laboratories and in industrial scenarios as well as interacting with humans in social activities. However, the design of engaging robotbased applications requires the availability of usable, flexible and accessible development frameworks, which can be adopted and mastered by researchers and practitioners in social sciences and adult end users as a whole. This paper surveys Visual Programming Environments aimed at enabling a paradigm fostering the so-called End-User Development of applications involving robots with social capabilities. The focus of this article is on those Visual Programming Environments that are designed to support social research goals as well as to cater for professional needs of people not trained in more traditional text-based computer programming languages. This survey excludes interfaces aimed at supporting expert programmers, at allowing industrial robots to perform typical industrial tasks (such as pick and place operations), and at teaching children how to code. After having performed a systematic search, sixteen programming environments have been included in this survey. Our goal is two-fold: first, to present these software tools with their technical features and Authoring Artificial Intelligence modeling approaches, and second, to present open challenges in the development of Visual Programming Environments for end users and social researchers, which can be informative and valuable to the community. The results show that the most recent such tools are adopting distributed and Component-Based Software Engineering approaches and web technologies. However, few of them have been designed to enable the independence of end users from high-tech scribes. Moreover, findings indicate the need for (i) more objective and comparative evaluations, as well as usability and user experience studies with real end users; and (ii) validations of these tools for designing applications aimed at working "in-the-wild" rather than only in laboratories and structured settings.

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Section: Block-based Interfacesmentioning

confidence: 99%

Visual Programming Environments for End-User Development of intelligent and social robots, a systematic review

Coronado

Mastrogiovanni

Indurkhya

et al. 2020

Journal of Computer Languages

Self Cite

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“…In order to solve the problem of time-varying parameters and disturbance in the system, many effective methods such as sliding mode control (12,13) , robust control (14,15) and intelligent control (16)(17)(18) were proposed. Subsequently, in order to solve the problems of pure time delay, time-varying parameters and disturbance in the system, many effective methods, such as sliding-mode Smith predictor method (19,20) , sliding-mode predictive control algorithm (21,22) , robust Smith predictive method (23,24) , robust predictive control algorithm (25,26) , Smith-fuzzy predictive control algorithm (27,28) and neural Smith predictive method (29,30) had been formed by combining sliding-mode control, robust control and intelligent control with Smith predictor method, and predictive algorithm.…”

Section: Introductionmentioning

confidence: 99%

Coordinated control of fuel flow rate and air flow rate of a supersonic heat-airflow simulated test system

2020

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ABSTRACTThe gas temperature of the supersonic heat airflow simulated test system is mainly determined by the fuel and air flow rates which enter the system combustor. In order to realise a high-quality control of gas temperature, in addition to maintaining the optimum ratio of fuel and air flow rates, the dynamic characteristics of them in the combustion process are also required to be synchronised. Aiming at the coordinated control problem of fuel and air flow rates, the mathematical models of fuel and air supply subsystems are established, and the characteristics of the systems are analysed. According to the characteristics of the systems and the requirements of coordinated control, a fuzzy-PI cross-coupling coordinated control strategy based on neural sliding mode predictive control is proposed. On this basis, the proposed control algorithm is simulated and experimentally studied. The results show that the proposed control algorithm has good control performance. It cannot only realise the accurate control of fuel flow rate and air flow rate, but also realise the coordinated control of the two.

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Adaptive cognitive robot using dynamic perception with fast deep-learning and adaptive on-line predictive control

Rincon

Coronado

Law

et al. 2019

Advances in Mechanism and Machine Science

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Expressive states with a robot arm using adaptive fuzzy and robust predictive controllers

Cited by 10 publications

References 14 publications

Visual Programming Environments for End-User Development of intelligent and social robots, a systematic review

Visual Programming Environments for End-User Development of intelligent and social robots, a systematic review

Coordinated control of fuel flow rate and air flow rate of a supersonic heat-airflow simulated test system

Adaptive cognitive robot using dynamic perception with fast deep-learning and adaptive on-line predictive control

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