Welcome to CRI Group Seminar Series!


CGSS #13: A robotic manipulation planning framework for next-generation manufacturing

Dr Wan Weiwei, School of Engineering Science, Osaka University, Japan
Friday 20 July 2018, 2pm, RRC Meeting Room (N3-01A-01)

Abstract

The working robots in factories are programmed to make repeated motions, which is not applicable to changing environments and varied objects. Even with most up-to-date vision systems, the flexibility of industrial robots is still highly restricted. This talk will present an AI-based framework. Given the models of objects and robots, the framework is able to automatically plan the grasping postures of robotic hands, plan the motion of manipulators, as well as plan the high-level action and assembly sequences. The framework automatically generates motions for industrial manipulators to perform varying tasks. Moreover, the framework employs Relational Database (RDB) to save the planned results, the relationships between objects and environments, the relationships between robotic hands and objects, and the relationships between robot manipulators and the hands, which enabled sharing data among different robots. The framework is expected to promote the replacement of human workers in next-generation manufacturing.

About the speaker

Weiwei Wan is an associate professor working at School of Engineering Science, Osaka University, Japan. Before joining at Osaka University, Weiwei was on a tenure-track position at the Manipulation Research Group, Intelligent System Research Institute, National Institute of Advanced Industrial Science and Technology (AIST) during 2015-2017. He was affiliated with the Japan Society for the Promotion of Science (JSPS) from 2013 to 2014 and did his postdoc research at the Manipulation Lab in the Robotics Institute, Carnegie Mellon University. Weiwei got his PhD in Robotics at the Department of Mechano-Informatics, The University of Tokyo in 2013. Weiwei’s major interest is smart manufacturing using dual-arm robots: Developing and deploying grasping planning, motion planning, and other low-level and high-level task planning algorithms for next-generation factories. Weiwei published more than 60 academic paper. He was the winner of IEEE Japan Chapter Young award in 2013, and the best paper award or finalist of several conferences. Weiwei serves in the editorial board of several journals and conferences (Transactions on Intelligent Technology (TIT), IROS, ROBIO, etc.). He also serves external funding reviewers for Research Grant Council (RGC) of Hong Kong and Isreal Science Foundation (ISF).


CGSS #12: 3D Bipedal Walking including COM height variations

Dr Stéphane Caron, IDH group, CNRS–University of Montpellier LIRMM, France
Monday 14 May 2018, 2pm, MAE Meeting Room C (N3.2-02-61)

Abstract

Real robots that walk in the field today rely on the Linear Inverted Pendulum Mode (LIPM) for walking control. Rigorously, the LIPM requires the robot's center-of-mass to lie in a plane, which is valid for walking on flat surfaces but becomes inexact over more general terrains. In this talk, we will see how to extend the LIPM to 3D walking, opening up old but refreshed questions on the analysis and control of bipeds. Technically, we will encounter a nonlinear control problem that we address by model predictive control of a quasi-convex optimization problem. We will see how the resulting controller works on the HRP-4 humanoid robot.

About the speaker

Stéphane Caron is a researcher in humanoid locomotion in the IDH group at CNRS–University of Montpellier LIRMM (France). An alumni of the École Normale Supérieure (ENS Paris), he received the Ph.D. in Mechano-Informatics from the University of Tokyo (Japan) in 2016, with a thesis on multi-contact motion planning for humanoid robots. His research interests include contact interaction, numerical optimization and model predictive control, all of which have applications in humanoid locomotion.


CGSS #11: An innovative open robotics platform to accelerate the development and adoption of robotics applications

Dr Thuc Vu, Ohmnilabs, USA
Thursday 22 March 2018, 2pm, RRC Meeting Room (N3-01A-01)

Abstract

Siloed development, wasted labor, and high start-up cost are limiting the pace of robotics innovation. With Kambria, our mission is to accelerate this process – enabling faster, cheaper, and easier robotics development and adoption by everyone. In this talk we will discuss the unique game-theoretical design of Kambria based on blockchain and crypto-economics to align the incentives of all key stakeholders in the robotics community. Ultimately, the Kambria platform will foster an ecosystem where collaborators, top developers, and companies, who share our passion for robotics technology will deliver affordable and impactful robots to end users. We will also give a quick demo of our first robot and an arm prototype manufactured based on 3D-printing technology. Overview: https://youtu.be/ayGuWHjPwvA.

About the speaker

Thuc is a serial entrepreneur, with multiple company acquisitions, the last one by Google. He has deep expertise in game theory, tournament design and multi-agent systems. He earned his PhD from Stanford and BS from Carnegie Mellon, both in computer science. Thuc is also a social entrepreneur in Vietnam, involved in several community projects.


CGSS #10: Interactive Sound Simulation and Rendering for VR/AR

Prof Dinesh Manocha, Department of Computer Science, University of North Carolina at Chapel Hill, USA
Friday 23 February 2017, 11am, IMI Seminar Room
(Held in conjuction with IMI Being There seminar)

Abstract

Extending the frontier of visual computing, sound rendering utilizes sound to communicate information to a user and offers an alternative means of visualization. By harnessing the sense of hearing, audio rendering can further enhance a user's experience in a multimodal virtual world and is required for immersive environments, computer games, engineering simulation, virtual training, and designing next generation human-computer interfaces.In this talk, we will give an overview of our recent work on sound propagation, spatial sound, and sound rendering. We describe new and fast algorithms for sound propagation based on improved wave-based techniques and fast geometric sound propagation. Our algorithms improve the state of the art in sound propagation by almost 1-2 orders of magnitude and we demonstrate that it is possible to perform interactive propagation in complex, dynamic environments by utilizing the computational capabilities of multi-core CPUs and many-core GPUs. We describe new techniques to compute personalized HRTFs and have integrated our algorithms the VR Headsets. Finally, we will give an overview of recent work on sound simulation in real-world scenes for augmented reality applications. We highlight their demonstration to indoor and outdoor scenes.

About the speaker

Dinesh Manocha is currently the Phi Delta Theta/Mason Distinguished Professor of Computer Science at the University of North Carolina at Chapel Hill. In Summer'2018, he will join University of Maryland at College Park as the Paul Chrisman Iribe Chair of Computer Science and Electrical/Computer Engineering. Manocha received his Ph.D. in Computer Science at the University of California at Berkeley 1992. He has published more than 480 papers and some of the software systems related to collision detection, GPU-based algorithms and geometric computing developed by his group have been downloaded by more than 200,000 users and are widely used in the industry. Along with his students, Manocha has also received 15 best paper awards at the leading conferences. He has supervised 33 Ph.D. dissertations and is a fellow of ACM, AAAS, AAAI, and IEEE. Manocha received Distinguished Alumni Award from Indian Institute of Technology, Delhi. He was a co-founder of Impulsonic, which was acquired by Valve, a leading VR and gaming company.


CGSS #9: Interactive multi-agent and avatar simulation for Social VR

Prof Dinesh Manocha, Department of Computer Science, University of North Carolina at Chapel Hill, USA
Tuesday 20 February 2017, 3pm, LT5
(Held in conjuction with CoE Distinguished Lecture)

Abstract

A key challenge in Social VR and crowd simulation is to generate natural-looking movements and behaviors of the virtual agents and human avatars. These include simulating full-body motions as well as interactions with the obstacles in the environment and other agents.
In this talk, we will present an overview of velocity-space planning algorithms to compute cooperative motion paths and behaviors for a group of independent agents, sharing the same space with other agents and avatars. These techniques include optimization-based strategies for distributed collision avoidance, the principle of least effort for simulating crowds, and data-driven models for capturing differences in personalities. We also describe efficient techniques for accurate simulations of large-scale crowds and methods to validate simulations against real-world data. We combine these methods with gait synthesis, NLP-based communication and gaze-based interaction to increase the sense of realism for Social VR.

About the speaker

Dinesh Manocha is currently the Phi Delta Theta/Mason Distinguished Professor of Computer Science at the University of North Carolina at Chapel Hill. In Summer'2018, he will join University of Maryland at College Park as the Paul Chrisman Iribe Chair of Computer Science and Electrical/Computer Engineering. Manocha received his Ph.D. in Computer Science at the University of California at Berkeley 1992. He has published more than 480 papers and some of the software systems related to collision detection, GPU-based algorithms and geometric computing developed by his group have been downloaded by more than 200,000 users and are widely used in the industry. Along with his students, Manocha has also received 15 best paper awards at the leading conferences. He has supervised 33 Ph.D. dissertations and is a fellow of ACM, AAAS, AAAI, and IEEE. Manocha received Distinguished Alumni Award from Indian Institute of Technology, Delhi. He was a co-founder of Impulsonic, which was acquired by Valve, a leading VR and gaming company.


CGSS #8: Vibration control of distributed parameter systems: from macro to micro scale

Dr Quoc Chi Nguyen, Control and Automation Laboratory, Ho Chi Minh University of Technology, Vietnam
Tuesday 13 June 2017, 10am, MAE Meeting Room C (N3.2-02-61)

Abstract

Vibration control of distributed parameter systems (DPSs), which represent many macro- and micro-scale devices, has been an important field of research. Vibration controls of macro-scale DPSs are focused on vibration suppression. Meanwhile, in the case of micro-scale DPSs, the micro devices are operated in vibration resonant modes, and the vibration amplitude is a control objective. There are two trends to develop the control schemes of the DPSs, in which they are classified by the uses of the continuous and discrete models in the control designs. DPSs describing by partial differential equations (PDEs) are referred as the continuous models, and the approximation of the PDE models are called as discrete models.

About the speaker

Quoc Chi Nguyen received the B.S. degree in Mechanical Engineering from Ho Chi Minh City University of Technology, Vietnam, in 2002, the M.S. degree in Cybernetics from Ho Chi Minh City University of Technology, Vietnam, in 2006, and the Ph.D. degree in Mechanical Engineering from the Pusan National University, Korea, in 2012. Dr. Nguyen was a Marie Curie postdoctoral fellow at the School of Mechanical Engineering, Tel Aviv University, from 2013 to 2014. He has been the head of Control and Automation Laboratory, Ho Chi Minh University of Technology since 2015. He also served as an IPC member at ICCAS’ 14,15,16,17 and ASCC 2017. Dr. Nguyen’s current research interests include MEMS control, nonlinear systems theory, adaptive control, robotics, and distributed parameter systems.


CGSS #7: A geometric perspective of anthropomorphic embodied actions

Dr Jean-Paul Laumond, LAAS-CNRS, France
Thursday 5 January 2017, 2pm, RRC Meeting Room (N3-01A-01)

Abstract

Starting from a mechanics point of view, the human (or humanoid) body is both a redundant system and an under-actuated one. It is redundant because the number of degrees of freedom is much greater than the dimension of the tasks to be performed: around 640 muscles for humans and 30 motors for humanoid robots. It is under-actuated because there is no direct actuator allowing the body to move from one place to another place: to do so human and humanoid robots should use their internal degrees of freedom and actuate all their limbs following a periodic process (named bipedal locomotion!).
By considering first that motions are continuous functions from time to space (i.e. trajectories), and second that actions are compositions of motions, actions appear as sequences of trajectories. The images of the trajectories in spaces are named paths. Paths represent geometric traces left by the motions in spaces. The reasoning holds for the real space, the configuration and the control space. Therefore actions appear as continuous simple paths in high dimensional spaces.
A simple path embodies the entire action. It integrates into a single data structure all the complexity of the action. The decomposition of the action into sub-actions (e.g., walk to, grasp, give) appears as the decomposition of the path into sub-paths. Each elementary sub-path is selected among an infinite number of possibilities within some sub-manifolds (e.g., grasp fast or slowly, grasp while bending the legs or not).
All complex cognitive and motor control processes that give rise to an action in the real world are reflected by the structure of paths in the body control space. In this framework, symbols may be defined as sub-manifolds that partition the control space. Such a partition decomposes paths into sub-paths. From this perspective the questions are:

  • Motion Segmentation: what are the invariant sub-manifolds that define the structure of a given action?
  • Motion Generation: among all the solution paths within a given sub-manifold (i.e. among all the possibilities to solve a given sub-task) what is the underlying law that converges to the selection of a particular motion?
The talk overviews recent results obtained in this framework (including whole body manipulation, locomotion trajectory generation, action recognition) and illustrated from the HRP2-14 humanoid platform.

About the speaker

Jean-Paul Laumond, IEEE Fellow, is a roboticist. He is Directeur de Recherche at LAAS-CNRS (team Gepetto) in Toulouse, France. He received the M.S. degree in Mathematics, the Ph.D. in Robotics and the Habilitation from the University Paul Sabatier at Toulouse in 1976, 1984 and 1989 respectively. From 1976 to 1983 he was teacher in Mathematics. He joined CNRS in 1985. In Fall 1990 he has been invited senior scientist from Stanford University. He has been a member of the French Comité National de la Recherche Scientifique from 1991 to 1995. He has been a co-director of the French-Japanese lab JRL from 2005 to 2008. He has been coordinator of two the European Esprit projects PROMotion (Planning RObot Motion, 1992-1995) and MOLOG (Motion for Logistics, 1999 - 2002), both dedicated to robot motion planning and control. In 2001 and 2002 he created and managed Kineo CAM, a spin-off company from LAAS-CNRS devoted to develop and market motion planning technology. Kineo CAM was awarded the French Research Ministery prize for innovation and enterprise in 2000 and the third IEEE-IFR prize for Innovation and Entrepreneurship in Robotics and Automation in 2005. Siemens acquired Kineo CAM in 2012. In 2006, he launched the research team Gepetto dedicated to Human Motion studies along three perspectives: artificial motion for humanoid robots, virtual motion for digital actors and mannequins, and natural motions of human beings. He teaches Robotics at Ecole Normale Supérieure in Paris. He has edited three books. He has published more than 150 papers in international journals and conferences in Robotics, Computer Science, Automatic Control and recently in Neurosciences. He has been the 2011-2012 recipient of the Chaire Innovation technologique Liliane Bettencourt at Collège de France in Paris. Here are the videos of the lectures, seminars and symposia. He is a member of the French Academy of Technologies. His current project Actanthrope (ERC-ADG 340050) is devoted to the computational foundations of anthropomorphic action.


CGSS #6: Motion planning for industrial robots and warehouse automation

Prof Dinesh Manocha, University of North Carolina at Chapel Hill, USA
Friday 9 December 2016, 11am, RRC Meeting Room (N3-01A-01)

Abstract

Algorithmic motion planning has been actively studied in robotics and related areas for more than three decades. In spite of considerable progress in terms of algorithmic techniques and applications, we need better planning systems that can deal  with the challenges that arise in the context of industrial robots and warehouse automation. These include dealing with sensor data, environmental uncertainties, robustly finding a desired path between different poses, realtime computations, and the safe trajectory planning in the presence of humans.
In this talk, we give a brief overview of our recent work to handle some of the problems. These include new optimization based methods that can compute smooth and collision-free trajectories for high DOF robots. We exploit the parallel capabilities of current CPUs and GPUs for realtime computation, and present new techniques for probabilities collision detection to handle environment uncertainties. We will demonstrate their application in developing a system, DoraPicker, an autonomous picking system. Finally, we will also present some preliminary results related to safe motion planning for robots working with or next to humans.

About the speaker

Dinesh Manocha is currently the Phi Delta Theta/Mason Distinguished Professor of Computer Science at the University of North Carolina at Chapel Hill.  He received his Ph.D. in Computer Science at the University of California at Berkeley 1992.   Along with his students, Manocha has also received 14 best paper awards at the leading conferences. He has published more than 400 papers and some of the software systems related to collision detection, GPU-based algorithms and geometric computing developed by his group have been downloaded by more than 150,000 users and are widely used in the industry. He has supervised 30 Ph.D. dissertations and is a fellow of ACM, AAAS, and IEEE. He received Distinguished Alumni Award from Indian Institute of Technology, Delhi.


CGSS #5: Collaborative artificial intelligence: optimisation problems with human-factor-based constraints

Dr Long Thanh-Tran, University of Southampton, UK
Tuesday 10 May 2016, 3pm, RRC Exhibition Room (N3-01A-01)

Abstract

With the recent fantastic breakthroughs in Artificial Intelligence (AI), such as the latest success of AlphaGo or the advancements in robotics, comes along an increasing number of concerns about the dangers and threats these Ai technologies may bring to our society. These concerns may become so serious in the future that it would cause serious harms to further advancements of AI research. In fact, the root of these concerns lies within the fear of creating a superhuman Artificial General Intelligence (AGI) that one day may decide to destroy the humankind.
To overcome these concerns, there have been many attempts to position AI as a set of more human-friendly and less threatening technologies. A very promising direction of these attempts is the concept of collaborative AI. This concept significantly differs from the AGI approach, as instead of focusing on creating superhuman competitors, it still keeps the human factor at the centre of its objectives. In particular, collaborative AI provides technologies that aim to ease our everyday life in a supportive and ubiquitous way. As ubiquitous systems, such as Internet of Things, and their applications (e.g., smart cities, smart homes, smart cars etc…) are becoming more and more successful, I argue that collaborative AI will also become a dominant concept in the (very) near future. However, state-of-the-art collaborative AI is still in its infant stage, and it will have to overcome a number of obstacles in order to achieve maturity. As such, in this talk, I will first describe in detail three major obstacles of the concept, namely: (i) human participation motivation; (ii) user privacy; and (iii) cyber security. In the second part of the talk, I will discuss the state-of-the-art research solutions within each above-mentioned topic. In particular, I will mainly focus on the problem of having the human-factor in optimisation problems, a research area I have been working on.

About the speaker

Long is currently with the University of Southampton, UK, where he is a Lecturer (Assistant Professor equivalent) in Computer Science. Long did his university studies in Budapest, Hungary (BME-VIK) and obtained his PhD from Southampton in 2012, under the supervision of Nick Jennings and Alex Rogers. He has been doing active research in a number of key areas of AI, mainly focusing on online machine learning, game theory, and incentive engineering. For his work, he has received a number of prestigious awards, such as: (i) the CPHC/BCS PhD Dissertation Award (for the best Computer Science PhD thesis in the UK in 2012/2013) - Honourable Mention; (ii) the ECCAI Artificial Intelligence Dissertation Award (for the best European PhD thesis in AI in 2012) - Honourable Mention; (iii) the Association for the Advancement of Artificial Intelligence (AAAI) Outstanding Paper 2012 Award - Honourable Mention; and (iv) the European Conference on Artificial Intelligence (ECAI) Best Student Paper 2012 Award - Runner-Up.


CGSS #4: Perspectives on motion planning and control for humanoid robots in multi-contact scenarios

Dr Stéphane Caron, Nakamura-Takano Laboratory, Department of Mechano-Informatics, University of Tokyo, Japan
Monday 07 March 2016, 3pm, RRC Meeting Room (N3-01A-01)

Abstract

When today's robots move around, the motion that you observe is the result of two software stages: planning and control. Planning is the part that computes a trajectory from the initial state of the system to some goal state. Control is the part that deals with perturbations or modelling errors, and stabilizes the system at best while it performs the trajectory output by the planner.
In this talk, we are going to explore the questions of planning and control for humanoid robots. We will see that straightforward formulations of the trajectory generation problem yield spaces of both high dimension and complex structure. We will then describe a number of solutions to "unwind" this structure into smaller sub-problems, which can be solved using a combination of stochastic and optimal-control algorithms.

About the speaker

Stéphane Caron was born in 1988 in Toulouse. He studied at École Normale Supérieure (Paris). After a one-year stay at the Technicolor Palo Alto Research Lab (California), he came to Japan to continue research in robotics. He graduated in 2016 after a 3-year PhD at the Nakamura Lab (University of Tokyo).


CGSS #3: UIUC Bio-engineering double seminar

Mr Aadeel Akhtar, MD/PhD Candidate, Neuroscience Program, University of Illinois at Urbana-Champaign and CEO, Co-Founder, PSYONIC
Mr Howard Liu, PhD Candidate, Department of Materials Science and Engineering, University of Illinois-Urbana Champaign, Urbana, IL 61801, USA, Frederick Seitz Materials Research Laboratory, Beckman Institute, Coordinated Science Laboratory, University of Illinois-Urbana Champaign, Urbana, IL 61801, USA
Thursday 21 January 2016, 10am, MAE Meeting Room D (N3.2-02-59)

Abstract

The Future of Upper Limb Prosthetics According to the WHO, roughly 80% of amputees live in low-income countries, while less than 3% of that population has access to appropriate rehabilitative care. In the first part of the talk, we will discuss our efforts in developing a highly-functional, low-cost, 3D-printed hand controlled by residual muscles for patients with transradial amputations, and our work with the Range of Motion Project in testing our device in Ecuador. The second part of the talk will focus on progress and challenges in incorporating proprioceptive and tactile sensory feedback into prosthetic hands.
Skin-Mounted Electronic Interfaces: From Materials to Circuit Considerations Flexible and stretchable forms of electronics provide new opportunities for integration with the human body, in ways that could enable high quality continuous monitoring and therapy. Challenges in this type of technology range from development of materials and devices that are compatible with polymer substrates, to circuit designs that offer robust operation in the presence of intrinsic device-to-device variability as well as changes induced by strains and deformations during use. Skin-mounted electronics systems that adopt the physical properties of the epidermis, sometimes referred to as epidermal electronic systems (EES) have unique capabilities in areas ranging from healthcare to human-machine interface. Such EES can provide passive sensing function, or active modalities, the latter of which requires sources of electrical power. In all cases, high performance devices are required, with circuit designs that can accommodate time dependent and time independent variations in properties. The technologies developed in our lab offer mechanical and geometrical characteristics that are outside of the scope of the rigid, brittle, planar integrated circuits that exist today. My current work focuses on biomedical sensors and actuators built using ultrathin membranes of inorganic materials, commercial off-the-shelf chips, and mechanically optimized structures that minimize strain-induced effects. Our work has relevance to establishment of materials and techniques for nanoprimitives, in the context of applications that demand advanced circuit design strategies for robust operation under property variations of the constituent components.

About the speakers

Aadeel is an M.D./Ph.D. candidate in the Neuroscience program at the University of Illinois at Urbana-Champaign. He is a member of the Bretl Research Group and currently holds an NIH National Research Service Award MD/PhD Fellowship. Aadeel received his B.S in Biology in 2007 and M.S. in Computer Science in 2008 at Loyola University Chicago. His research interests include motor control and sensory feedback for upper limb prosthetic devices, and he has established collaborations with the Rehabilitation Institute of Chicago, the John Rogers Research Group at Illinois, and the Range of Motion Project in Guatemala and Ecuador. He is also the Co-Founder and CEO of PSYONIC, a startup whose mission is to develop advanced, neurally-controlled prosthetic hands—the first with sensory feedback—at a tenth the cost of state-of-the-art commercially available prostheses, for those who need them around the world.
Howard Liu is a PhD Candidate in Department of Materials Science and Engineering at University of Illinois Urbana Champaign under supervision of John A. Rogers. He received his B.S. in the Department of Materials Science and Engineering from University of California Berkeley, where he spent two years as research assistant in Chancellor Robert J. Birgeneau’s lab focusing on iron-based high Tc superconducting materials. After graduation, he works in Advanced Light Source at Lawrence Berkeley National Laboratory as a Synchrotron beamline assistant until he begins his PhD study at University of Illinois. His current research interest spans interdisciplinary fields of materials, bioengineering, electronics and nanotechnology with primary focus on advanced fabrication and processing strategies of bio-inspired and bio-integrated epidermal devices for healthcare applications. He has published over 20 peer-reviewed articles and received global recognitions and awards in research and teaching. He is an active student representative in higher education administration and executive searching committees to create impacts in local community.


CGSS #2: Next generation gripper technology with sensor

Mr Yoshiaki Tatsumi, CEO and head of R&D, Creative Technology Corporation, Japan
Wednesday, August 13th 2014, 2pm-3pm, MAE Meeting Room B (N3-02b-65)

Abstract

Creative Technology Corporation, Japan, is a company founded in 1985. Its main business concerns the research, development and production of components for semiconductor manufacturing (surface treatment, bonding, evaluation, measures). More information at http://www.createch.co.jp/english/company/company_information.html
The topics of this seminar are:
  1. Electrical Gripper with capacitance sensor
  2. Chucking system with Ion Pad (Van der Waals force)
  3. Flexible Electric Capacitance Sensor
  4. Acoustic Emission Sensor
  5. Chucking system in water with sensor
  6. Introduction for development of environment using a 6 axis articulated robot


CGSS #1: Presentation of Denso industrial robots and software

Mr Toshihiro Inukai, General Manager (Software), Denso Wave Inc. Japan
Friday, May 9th 2014, 2pm-3pm, RRC1 (N3-01A-01)

Abstract

Denso Corporation is one of the largest automotive components manufacturers worldwide. Denso Wave is a subsidiary of Denso Corporation specialized in particular in industrial robots. The topics of this seminar are:
  1. Introduction of Denso and Denso Robots;
  2. Introduction of Denso RC8/MC8 Controller (the latest Denso robot controller);
  3. Introduction of Denso Robot solution platform using Open Source Software.