Scientific Program

Conference Series Ltd invites all the participants across the globe to attend 6th World Convention on Robots, Autonomous Vehicles and Deep Learning Singapore.

Day 2 :

Keynote Forum

Soo yeung lee

Korea Advanced Institute for Science and Technology, Republic of Korea

Keynote: Digital Companion with Human-like Emotion and Ethics

Time : 09:30-10:15

OMICS International Smart Robotics congress 2018 International Conference Keynote Speaker Soo yeung lee photo

Soo-Young Lee has worked on the artificial cognitive systems with human-like intelligent behavior based on the biological brain information processing. His research includes speech and image recognition, natural language processing, situation awareness, top-down attention, internal-state recognition and human-like dialog systems. Especially, among many internal states, he is interested in emotion, sympathy, trust and personality. He led Korean Brain Neuroinformatics Research Program from 1998 to 2008 with dual goals, i.e., understanding brain information processing mechanism and developing intelligent machine based on the algorithm. He is currently the Director of KAIST Institute for Artificial Intelligence and leading Emotional Conversational Agent Project and a Korean National Flagship AI Project. He was the President of Asia-Pacific Neural Network Society in 2017 and had received Presidential Award from INNS and Outstanding Achievement Award from APNNA.



For the successful interaction between human and digital companion, i.e., machine agents, the digital companions need be able to bind with human-like ethics as well as to make emotional dialogue, understand human emotion and express its own emotion. In this talk we present our approaches to develop human-like ethical and emotional conversational agents as a part of the Korean Flagship AI Program. The emotion of human users is estimated from text, audio and visual face expression during verbal conversation and the emotion of intelligent agents is expressed by speech and facial expression. Specifically, we will show how our ensemble networks won the Emotion Recognition in the Wild (EmotiW2015) challenge with 61.6% accuracy to recognize seven emotions from facial expression. Then, a multimodal classifier combines text, voice and facial video for better accuracy. Also, a deep learning based Text-to-Speech (TTS) system will be introduced to express emotions. These emotions of human users and agents interacts each other during the dialogue. Our conversational agents have chitchat and Question-and-Answer (Q&A) modes and the agents respond differently for different emotional states in chitchat mode. Then, the internal states will be further extended into trustworthiness, implicit intention and personality. Also, we will discuss how the agents may learn human-like ethics during the human-machine interactions.

Keynote Forum

Mingcong Deng

Tokyo University of Agriculture and Technology JAPAN

Keynote: Operator-based nonlinear control of micro hand and its application

Time : 10:15 -11:00

OMICS International Smart Robotics congress 2018 International Conference Keynote Speaker Mingcong Deng photo

Prof. Mingcong Deng is a Professor of Tokyo University of Agriculture and Technology, Japan. He received his PhD in Systems Science from Kumamoto University, Japan, in 1997. From 1997.04 to 2010.09, he was with Kumamoto University; University of Exeter, UK; NTT Communication Science Laboratories; Okayama University. Prof. Deng is a member of SICE, ISCIE, IEICE, JSME, IEEJ and the IEEE(SM). He specializes in three complementary areas: Operator based nonlinear fault detection and fault tolerant control system design; System design on thermoelectric conversion elements; Applications on smart material actuators. Prof. Deng has over 460 publications including 158 journal papers, 15 books (or chapters), in peer reviewed journals including IEEE Transactions, IEEE Press (for books) and other top tier outlets. He serves as a chief editor for International Journal of Advanced Mechatronic Systems, The Global Journal of Technology and Optimization, and associate editors of 6 international journals, including with IEEE journal. Prof. Deng is a co-chair of agricultural robotics and automation technical committee, IEEE Robotics and Automation Society; also a chair of the environmental sensing, networking, and decision making technical committee, IEEE SMC Society. He was the recipient of 2014 Meritorious Services Award of IEEE SMC Society.


Soft actuators have been getting increased attention with developing of medical fields etc. A miniature pneumatic bending rubber actuator is one of the soft actuators. The actuator has the bellows shape and are made of silicone rubbers. Due to the bellows shape, the actuator can do two-way large bending by supplying positive or negative air-pressure. However, to control the actuator and make its model accurately are difficult because the actuator has nonlinearity. Moreover, the actuator should be controlled without sensor because its expected application are medical fields, especially, in operations. On the other hand, a control system based on operator theory can apply nonlinear systems with uncertainties. The relationship between operator theory and passivity or adaptive control which is an important idea in control engineering has discussed by some researchers. Meanwhile, support vector regression (SVR) has been utilized for classification and regression analysis, where the design parameters are selected by using particle swarm optimization (PSO). Therefore, operator-based control system is discussed. In order to realize sensorless control, PSO-SVR-based moving estimation with generalized Gaussian distribution (GGD) kernel is employed. That is, operator-based sensorless adaptive nonlinear control system considering passivity for the actuator and PSO-SVR-based moving estimation with GGD kernel are shown. Finally, some simulations and experimental results are introduced.

Keynote Forum

Qingsong Xu

University of Macau, China

Keynote: Design and Application of Force-Sensing Robotic Bio-Micromanipulation Systems

Time : 11:15-12:00

OMICS International Smart Robotics congress 2018 International Conference Keynote Speaker Qingsong Xu photo

Qingsong Xu is the Director of Smart and Micro/Nano Systems Laboratory and Associate Professor of Electromechanical Engineering at the University of Macau. He was a Visiting Scholar at the University of California, Los Angeles (UCLA), USA in 2016, the RMIT University, Melbourne, Australia in 2016, the National University of Singapore, Singapore in 2012 and the Swiss Federal Institute of Technology (ETH Zurich), Switzerland in 2011. His current research area involves micro/nano-mechatronics and systems, control and automation and applications of computational intelligence. He is a Senior Member of IEEE and a Technical Editor of IEEE/ASME Transactions on Mechatronics. He has published three monographs and over 240 technical papers in international journals and conferences.


Robotic micromanipulation systems are demanding devices to realize automated manipulation of biological samples. Majority of existing robotic bio-micromanipulation systems work based on displacement sensing and control. The lack of force sensing prevents the wide application of the devices. In modern biotech industry, there are increasing needs for advanced micromanipulation equipment with microforce sensing and control capabilities. The development of force-sensing microinjectors and microgrippers enable extensive applications involving biological field with guaranteed safety and accuracy of advanced robotic manipulation. This talk reports our recent work on design and development of new force-sensing robotic micromanipulation systems dedicated to biological micromanipulation tasks. In particular, force-sensing microinjector and force-sensing microgripper are presented as typical examples. New microforce sensor design is conducted in details. Novel control schemes have been developed to fuse the position and force control to enable a safe and reliable manipulation. The effectiveness of the systems has been demonstrated by carrying out microinjection and microgripping operation of biological cells. The developed force-sensing robotic bio-micromanipulation systems have demonstrated wide applications in the fields of biomedical engineering, gene engineering and so on.

Keynote Forum

Manchita Dumlao

The Philippine Women’s University, Philippines

Keynote: Central emergency response management system

Time : 12:00-12:45

OMICS International Smart Robotics congress 2018 International Conference Keynote Speaker Manchita Dumlao photo

Menchita F Dumlao is currently the Research Director of Philippine Women’s University, Philippines. Concurrently, she is an Associate Professor and Program Chair of Department of Information Technology and Technology Consultant of Imergex Information Technology, Inc. Her research interest is in the area of data science, machine learning and artificial intelligence.




Central Emergency Response Management system (CERM) facilitates estimation of dispatch response time and route or direction from the origin of the resource to incident site. The dispatch determined the capability required to a specific incident. Its core technology is Call Taking Management System (CTMS) which applies stochastic optimization to collaborate sub-systems and make everything else complete. They are connected end to end to create a consolidated database system leading to a criminal information system and incident command system which includes call taking and logging module, resource unit dispatch and geo-mapping module, SMS messaging services module, resource availability and dispatch. It can record audio patch from the telephone line through the audio input of the PC (client computer). The provided information on incident, incident type, location and other important information needed by the dispatcher (police). The map provides an aerial view (satellite image) of the location of an incident for the nearest equivalent search parameter within 10,000 meters from the center of crime. This technology shows the best route possible from the unit resource (of the crime) origin to the incident site. The control also shows text-based instruction, estimated time and distance.