Industry meets research: munich_i offers you the unique opportunity to experience the world's leading technology experts in the area of robotics and AI in a single day. Each of them is considered a visionary from this innovative international industry and represents the development of new technological standards. Or in other words: They build the required bridges between high-tech and practical applications. For you this means: first-hand pioneers’ knowledge.
Anna is a Bioinformatician by training and leads the Data Science Department in Roche Pharma Research and Early Development in Germany. Her team supports pre-clinical and clinical research teams through data management and data analysis, applying in particular Artificial Intelligence methods. We are analyzing high-dimensional data such as imaging data, genomic information, and data from electronic health records to better understand diseases and develop personalized therapies.
Wolfram Burgard is a Professor of Computer Science at the University of Technology Nuremberg, Germany, where he heads the research group for Robotics and Artificial Intelligence. From 2019 until 2021 he was VP for Automated Driving Technology and Machine Learning at the Toyota Research Institute in Los Altos, CA, USA. Wolfram Burgard is known for his contributions to robot navigation, perception, manipulation, and learning.
For autonomous robots and automated driving, the capability to robustly perceive environments and execute their actions is the ultimate goal. The key challenge is that no sensors and actuators are perfect, which means that robots and cars need the ability to properly deal with the resulting uncertainty. In this presentation, I will introduce the probabilistic approach to robotics, which provides a rigorous statistical methodology to deal with state estimation problems. I will furthermore discuss how this approach can be extended using state-of-the-art technology from machine learning to deal with complex and changing real-world environments.
Ewa leads Product Management team for Product Engineering Cloud Artificial Intelligence team at Google, California. Before Google, Ewa was an entrepreneur and led product management, innovation and business development at the SaaS start-up, impacore GmbH.
Ewa owns an MBA from Harvard Business School and has a multi-year experience as a management consultant in Bain & Co., World Bank/ Rwanda Development Board and A.T. Kearney. She brings in global perspective: worked and studied across six continents (Europe, LatAm, North America, Africa, Asia and Australia) and is fluent in six languages (native: Polish, fluent English, German, Spanish, Italian, Russian).
Interestingly, Ewa used to professionally play in the orchestra as first violinist and is a passionate marathon runner, motorcycle rider and holder of a helicopter private pilot license.
As an industry, we’ve managed to transition artificial intelligence (AI) from ‘research’ to a technology that is a part of the lives of countless people around the world. In this session we will talk about how enterprises have embraced AI and the power this technology has for the future. At the same time, we recognize that powerful AI technology raises equally powerful questions about its use. As leaders in AI, we feel a deep responsibility to get this right and will talk about principles, governance and fairness of AI, highlighting some of the best practices.
Seth Hutchinson is the Executive Director of the Institute for Robotics and Intelligent Machines at the Georgia Institute of Technology, where he is also Professor and KUKA Chair for Robotics in the School of Interactive Computing. His research in robotics spans the areas of planning, sensing, and control. He has published widely on these topics, and is coauthor of the books "Robot Modeling and Control," published by Wiley, and "Principles of Robot Motion: Theory, Algorithms, and Implementations," published by MIT Press.
The lack of cognitive capabilities and the performance of industrial sensors have been the bottleneck for robot applications in and outside of the industry since decades. Whereas computational power and memory capacity have grown substantially and motors and drivers have turned bulky robots into high precision fast moving light weight kinematic machines, the cognitive capabilities to understand and interpret the robot’s environment have not been growing with the same pace. But data of physical, geometrical and even mental status of the environment are essential to feed the well-known and powerful AI algorithms in applications outside of the well-defined industrial world. The presentation will document the state of the art and gives some trends, visions and requirements for the next generation of sensors that will help to increase cognitive capabilities to a further level.
Jens Kober is an associate professor at the TU Delft, Netherlands. He worked as a postdoctoral scholar jointly at the CoR-Lab, Bielefeld University, Germany and at the Honda Research Institute Europe, Germany. He graduated in 2012 with a PhD Degree in Engineering from TU Darmstadt and the MPI for Intelligent Systems. For his research he received the annually awarded Georges Giralt PhD Award for the best PhD thesis in robotics in Europe, the 2018 IEEE RAS Early Academic Career Award, and has received an ERC Starting grant. His research interests include motor skill learning, (deep) reinforcement learning, imitation learning, interactive learning, and machine learning for control.
The acquisition and self-improvement of novel motor skills is among the most important problems in robotics. We will discuss various learning techniques we developed that enable robots to have complex interactions with their environment and humans. Complexity arises from dealing with high-dimensional input data, non-linear dynamics in general and contacts in particular, multiple reference frames, and variability in objects, environments and tasks.
A human teacher is always involved in the learning process, either directly (providing data) or indirectly (designing the optimization criterion), which raises the question: How to best make use of the interactions with the human teacher to render the learning process efficient and effective?
We will discuss various methods we have developed in the fields of supervised learning, imitation learning, reinforcement learning, and interactive learning. All these concepts will be illustrated with benchmark tasks and real robot experiments ranging from fun (ball-in-a-cup) to more applied (sorting products).
Cecilia Laschi is Professor at the National University of Singapore, in the Department of Mechanical Engineering. She is on leave from Scuola Superiore Sant'Anna, Italy, The BioRobotics Institute (Dept. of Excellence in Robotics & AI). She graduated in Computer Science at University of Pisa and received a Ph.D. in Robotics from the University of Genoa. She was JSPS visiting researcher at Waseda University in Tokyo.
Her research interests are in soft robotics, an area she pioneered and contributed to develop internationally, including its marine and biomedical applications. She has been working in humanoid and neuro-robotics.
She is Editor-in-Chief of Bioinspiration & Biomimetics and she serves in the Editorial Boards of many journals, including Science Robotics and serves as reviewer for journals like Nature and Science, for EC (incl. ERC), HFSP and national research agencies.
She is member of AAAS, senior member of IEEE, EMBS and RAS, where she is AdCom member and co-chair of TC on Soft Robotics. She founded and chaired the 1st IEEE-RAS Int. Conf. on Soft Robotics.
She co-founded the spin-off RoboTech srl.
Robotics technologies have reached a level of performance and reliability that are uncommon in other technological fields. Robots are helpful in factories, in hospitals, underwater and in the sky. They have a huge potential to help us at home, in our cities and in our daily activities, but not yet fully ready for that. Robots are complex systems, requiring important amounts of energy and computation to work properly.
If we turn our eyes towards living beings, we see systems that look simple in their behaviour, in natural environments, efficient, flexible and adaptable to unexpected situations. Yet, they are in fact way more complex than our robots. What are the principles for making complex systems simple in their behaviour? This is the lesson that we can learn from Nature, in robotics. We learn that intelligence is not only in brain and computation, but also in the body. A soft body can help take advantage of such embodied intelligence and reduce computation and energy needs.
Soft robotics has been growing fast in recent years and producing a variety of technologies for building robots with soft materials and compliant structures. Bioinspired soft robotics is enabling robot abilities that were not possible before, like morphing, stiffening, growing, self-healing, evolving. Soft robots find applications in many fields, from medicine to underwater explorations. We can envisage future scenarios with robots that are more life-like and better integrated in our natural world, contributing to a more humane relations with people and a fairer relation between technology and nature.
Laura Marchal-Crespo is Associate Professor at the Department of Cognitive Robotics, Faculty 3mE (Mechanical, Maritime and Materials Engineering), Delft University of Technology, Netherlands. Her research focuses on the general areas of human-machine interaction and biological learning and, in particular, the use of robotic devices and immersive virtual reality for the assessment and rehabilitation of patients with acquired brain injuries such as stroke. A major goal of her research is to gain a better understanding of the underlying mechanisms associated with the acquisition of novel motor skills in order to develop innovative technology to improve neurorehabilitation. She develops intelligent controllers that modulate movement errors based on patients’ special needs, age, and training task characteristics using a wide selection of robotic devices for upper and lower limb rehabilitation. She further employs electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) to identify neurocognitive markers underlying motor learning.
The possibility of using robotic devices and virtual reality to support motor learning and neurorehabilitation is promising since robots can deliver high-intensity training in a motivating and safe virtual environment. However, recent meta-analyses concluded that traditional robotic training yields similar or even inferior outcomes to conventional therapy, especially in activities in daily living. This is not surprising, since current rehabilitation robots only provide general assistance, independent of patients’ individual needs, to perform rather artificial movements that are far from being functional.
Matthew T. Mason is the Chief Scientist at Berkshire Grey. He earned the BS, MS, and PhD degrees at the MIT AI Lab. At Carnegie Mellon University he served ten years as Chair of the Robotics PhD program, and another ten years as Director of the CMU Robotics Institute. He is a Fellow of the AAAI, the IEEE, and the ACM. He is a winner of the System Development Foundation Prize, the IEEE RAS Pioneer Award, and the 2018 IEEE Technical Field Award in Robotics and Automation.
This talk tells the Berkshire Grey story, how it adapted robotics technology from research labs to transform warehouses and distribution centers, leading to a public listing on NASDAQ -- the first since iRobot 15 years ago. Berkshire Grey produces automated systems for e-commerce order fulfillment, parcel sortation, store replenishment, and related operations in warehouses, distribution centers, and in the back ends of stores. The talk will discuss the fundamental issues in warehouse automation, the technology and solutions developed by Berkshire Grey, and future challenges.
Giorgio Metta is the Scientific Director of the Istituto Italiano di Tecnologia (IIT). He holds a MSc cum laude (1994) and PhD (2000) in electronic engineering both from the University of Genoa. From 2001 to 2002, Giorgio was postdoctoral associate at the MIT AI-Lab. He was previously with the University of Genoa and from 2012 to 2019 Professor of Cognitive Robotics at the University of Plymouth (UK). He was member of the board of directors of euRobotics aisbl, the European reference organization for robotics research. Giorgio Metta served as Vice Scientific Director of IIT from 2016 to 2019. He coordinated IIT's participation into two of the Ministry of Economic Development Competence Centers for Industry 4.0 (ARTES4.0, START4.0). He was one of the three Italian representatives at the 2018 G7 forum on Artificial Intelligence and, more recently, one of the authors of the Italian Strategic Agenda on AI. Giorgio coordinated the development of the iCub robot for more than a decade making it de facto the reference platform for research in embodied AI. Presently, there are more than 40 robots reaching laboratories as far as Japan, China, Singapore, Germany, Spain, UK and the United States. Giorgio Metta research activities are in the fields of biologically motivated and humanoid robotics and, in particular, in developing humanoid robots that can adapt and learn from experience. Giorgio Metta is author of more than 300 scientific publications. He has been working as principal investigator and research scientist in about a dozen international research as well as industrial projects.
This talk covers two main research directions based on the iCub humanoid robot. The iCub is a humanoid robot designed to support research in embodied AI. The iCub is being used at the Italian Institute of Technology as a model platform to develop the technology of future interactive service robots. In particular, I will describe our work in the field of physical and social interaction. For example, through extensive use of machine learning, we developed algorithms to interpret and use external contact information in a variety of tasks as well as contactless cues – vision, sound – to ease interaction between the user and the robot.
Dominik Metzger is part of the SAP Product Engineering organization for Digital Supply Chain and works as Head of Product Management for Manufacturing & Industrial IOT. A key cornerstone of SAPs Digital Supply Chain strategy is to bring significant productivity increase and cost reduction to customers with the capabilities of Industry 4.0. SAPs Industry 4.0 strategy is called Industry 4.Now with a high focus on Intelligent Products, Intelligent Factories/Plants, Intelligent Assets and Empowered People based on technology enablers with the Industrial IOT.
Manufacturing companies, in both discrete and process industries, are experiencing an increase in the complexity of their operations. These complexities are caused, amongst others, by significant supply chain disruptions across the entire value chain of manufacturers and their network of contractors and suppliers. Examples include supply shortages e.g. caused by logistical disruptions or a lack of raw materials and components due to macro-economic impacts. At the same time, it is expected for manufacturers to comply to each increasing requirements around traceability. In many industries, such as life sciences or consumer products, this has been a default. For other industries, such as automotive or industrial machinery, the capability to trace the root cause for a machine failure is becoming more and more important. While in the last 10-15 years a huge emphasis has been on factory automation, the new mega-trend, that we will discuss in this session, is the network-aware factory. Network awareness allows factories to anticipate and react to supply chains disruptions with much more agility while providing an end-to-end parts and material traceability across value chains.
Lucia Pallottino is currently Associate Professor at the Centro di Ricerca "E. Piaggio" and the Dipartimento di Ingegneria dell'Informazione at the University of Pisa. She received the "Laurea" degree in Mathematics (1998) and a Doctoral degree in Robotics and Industrial Automation (2002). She has been Visiting Scholar at M.I.T. (2000-2001) in the Laboratory for Information and Decision Systems (LIDS ). She has been Visiting Researcher at UCLA, (2004) in the Mechanical and Aerospace Engineering Department (MAE).
Since its birth 60 years ago, robotics has witnessed a large growth and profound change in scope: from segregated robots in the past, to robots that currently are close to, and even in touch with humans. Indeed, both cognitive and physical human–robot interactions are largely studied in Robotics. Moreover, large systems of autonomous but networked units, capable of acting in and on the environment, will soon be a reality. Robots will be many, autonomous, possibly fast, and very heterogeneous. Hence, another fundamental aspect that must be faced is the robot–robot interaction. The goal is to understand how large numbers of robots, differing in their bodies, sensing, and intelligence, may be made to coexist, communicate, collaborate or compete fairly toward achieving their individual goals, i.e., to build a society of robots.
In this talk, we will discuss the main challenges in multi-robot collaboration and coordination showing examples of possible approaches in different applications areas and with both mobile robots and manipulators.
Dr. Christoph Peylo leads the project “Digital Trust” in Bosch’s CDO organization. Before that he established and lead Bosch’s Center for Artificial Intelligence (BCAI). He was member of the high-level expert group on AI of the European Commission. Prior to joining Robert Bosch GmbH in 2017 he worked at Deutsche Telekom Laboratories in Berlin in the area of AI, Cybersecurity, Industrie 4.0, and IoT.
Before joining Deutsche Telekom in 2006 he worked in various positions from software engineer to managing director of a software company.
Christoph Peylo has studied Computer Science, Computational Linguistics and Artificial Intelligence and acquired his Ph.D. at the University of Osnabrück in the field of AI.
The physical world offers a sufficiently stable and agreed on basis for most human interactions, since human beings, by and large, share a similar set of mechanisms to perceive the world and interact with and communicate about it. Therefore, the underlying ontological commitments and assumptions of statements like “trust”, “believe” etc., can, most of the time, be taken for granted and do not have to be explained explicitly.
This, however, is not the case within the digital world. What commonly is referred to as “digital world”, is only loosely defined by agreed on protocols on a communication network, e.g. the Internet, and tools, services, and applications to communicate and interact with networked devices. Protocols, tools and underlying networks are under constant development and change, so the digital world is an extremely brittle environment.
Thus, “digital trust” will not work as a simple mapping of the relevant dimensions of “trust” to their respective digital representations in an existing digital world, since there is no stable digital world. And AI brings in even more volatility. The respective domain and scope of “trust” and the relationship of the involved entities have to be defined and created for any context in which trustworthy digital interactions should take place. Thus, “Digital Trust” specifies the relationship between two entities with respect to a specific task that requires entitlement, competence and adherence to certain pre-defined standards, protocols or principles. For keeping track of the expectations, learning from experience and adapt to specific behavior patterns, AI is an extremely powerful technology. Thus, AI can support to establish Digital Trust by adapting a digital product or service to the individual expectations of people during the whole life cycle of a product.
Experiencing “Digital Trust” will be the corresponding digital counterpart of today’s core quality and value proposition of the non-digital world.
Dr. Alfred Rizzi is currently the Chief Scientist at Boston Dynamics where he directs research and product development based on novel locomotion and mobile manipulation systems. Prior to joining Boston Dynamics, in 2006, he was an Associate Research Professor in the Robotics Institute at Carnegie Mellon University where he directed research projects focused on hybrid sensor-based control of complex and distributed dynamical systems. Dr. Rizzi received the Sc.B, degree in electrical engineering from the Massachusetts Institute of Technology in 1986. He received the M.S. and Ph.D. from Yale University in 1990 and 1994 respectively.
At Boston Dynamics over the past decade we have made significant progress in developing locomotion capability that rivals humans and animals. One important feature of these systems is that they are easy for an operator to drive, giving users the ability to access a significant fraction of the world that was previously inaccessible via wheeled and tracked robots. As we begin to deliver legged mobile robots with arms and grippers we seek to do the same thing in the mobile manipulation space and provide reactive control strategies that allow users/operators and higher level control systems to effectively use a robot to reliably interact with its environment to pick, place, grasp, and manipulate useful objects.
Ferdinando Rodriguez y Baena is Professor of Medical Robotics in the Department of Mechanical Engineering at Imperial College, where he leads the Mechatronics in Medicine Laboratory and the Applied Mechanics Division. He has been the Engineering Co-Director of the Hamlyn Centre, which is part of the Institute of Global Health Innovation, since July 2020. He is a founding member and great advocate of the Imperial College Robotics Forum, now the first point of contact for roboticists at Imperial College.
His 20-strong team of staff and PhD students has a translational focus, though their work encompasses both “blue skies” research and “near-to-market” development. He is the Chair of the Programme Committee for the International Society for Computer Assisted Orthopaedic Surgery (CAOS International), CAOS UK, and the Hamlyn Symposium; He is also the founding Chair of the IET’s recently established Communities Committee for Technical Networks (CC TN), a Leverhulme Prize winner (engineering), a former ERC grant holder, and the coordinator of an €8.3M European project on robotic-assisted neurosurgical drug delivery (EDEN2020). He has published over 160 papers and secured in excess of £12M in research funding to date.
Surgical technology has experienced steady growth over the past three decades, with the widespread adoption of computer navigation and robotics finally on the horizon. Fuelled by unique experiences in technological development, clinical deployment and commercialisation, this talk will provide a unique take on the ups and down of surgical robotics research, followed by a glimpse into the future of this technology, with examples of new mechanisms, control strategies, visualisation technologies and machine learning schemes currently under development at Imperial College.
Dr. Wen Tong is the CTO, Huawei Wireless. He is the head of Huawei wireless research. In 2011, Dr. Tong was appointed the Head of Communications Technologies Labs of Huawei, currently, he is the Huawei 5G chief scientist and led Huawei’s 10-year-long 5G wireless technologies research and development.
Prior to joining Huawei in 2009, Dr. Tong was the Nortel Fellow and head of the Network Technology Labs at Nortel. He joined the Wireless Technology Labs at Bell Northern Research in 1995 in Canada.
Dr. Tong is the industry recognized leader in invention of advanced wireless technologies, Dr. Tong was elected as a Huawei Fellow and an IEEE Fellow. He was the recipient of IEEE Communications Society Industry Innovation Award in 2014, and IEEE Communications Society Distinguished Industry Leader Award for “pioneering technical contributions and leadership in the mobile communications industry and innovation in 5G mobile communications technology” in 2018. He is also the recipient of R.A. Fessenden Medal. For the past three decades, he had pioneered fundamental technologies from 1G to 5G wireless with more than 510 awarded US patents.
Dr. Tong is a Fellow of Canadian Academy of Engineering, and he serves as Board of Director of Wi-Fi Alliance.
The emerging 6G connectivity with the new capabilities such as integrated sensing and communications with Tera-Hertz frequency and networked machine learning can enable a new paradigm of cloud robots. With the low latency and high reliability 6G wireless connectivity, we can re-architect the collaborative robots, interactions of the robots and even the tactile sensing with virtualized cloud-based AI, the advantage of the 6G intelligent robots will allow the unification of a global platform the for sensing, communications, computing and control and anywhere and anytime.
Melonee Wise is the Vice President of Robotics Automation at Zebra Technologies. Melonee joined Zebra through the acquisition of Fetch Robotics where she was the CEO. Melonee was the second employee at Willow Garage where she led a team of engineers developing next-generation robot hardware and software, including ROS, the PR2, and TurtleBot. Melonee serves as the Chair of the IFR Service Robot Group, as a robotics board member for A3, and on the MHI Roundtable Advisory Committee. Melonee has received the MIT Technology Review’s TR35 and has been named to the Silicon Valley Business Journal’s Women of Influence and 40 Under 40, the Robotics Business Review RBR50, and as one of eight CEOs changing the way we work by Business Insider.
A look into how robots perceive the world that they work in and the impact of their understanding of the world when working with people and human operated machines.