Design selected by nature is based on evolution and we can get an idea how to design the robot. There are various designs of robot in different scale inspired by nature. However, micro- and nano-scaled robots are still very difficult to realize. It is a big challenge to realize micro- and nano-scaled robots as well as to realize automation of several tasks in micro- and nano-scales. We need to study multidisciplinary research field for innovation. Here we would emphasize importance of micro-nanomechatronics for system integration.

Micro- and nano-scaled robots are promising tools for (1) analytical purposes and (2) medical purposes. For analytical purposes, they are often used for the scientific exploration, such as investigation of unknown properties of biological cells, and so on. For medical purposes, they are often used for the noninvasive medical treatments including long-term delivery of medication and painless pinpoint surgery, and so on.

For analytical purposes, we have studied on the robotics and automation in micro- and nano-scales by integrating robotics and microfluidics. On-chip Robotics (= “Robotics” x “ Microfluidics”) is an interdisciplinary research area. We have studied on an on-chip robot system which is a microfluidic chip system integrated with sensors and actuators based on the robotic technology since 1999. The on-chip robot systems have great potential to achieve several tasks, such as powerful and accurate cell manipulation for broad range of biomedical applications with high throughput and dexterity. Here we can take advantage of hydrodynamic interaction as well as mechanical interaction in/on the chip. Emerging functions by integration of both robotic and microfluidic technologies have been studied and applied to the tasks for several scientific experiments, such as secure manipulation of biological single-cells, measurement of physiological conditions and mechanical properties of cells, separation of cells with high throughput, insertion of micropipette into the cell with high accuracy, and so on. In these applications, Micro-nanomachatronics plays an important role to realize advanced functions and automation.

For medical purposes, the micro- and nano-scaled robots, which can autonomously explore the human body through the vascular system and performing medical tasks, have attained great attention. Since the size of the robot is very small, driving methods of the robot for propulsion, actuation, and manipulation are very important and key issues of research. As the design method of the micro-robotic system, driving methods for the cable-less micro-robot will be focused for innovation in this field.

In summary, robotics and automation in micro- and nano-scales and contribution of Micro-nanomachatronics will be introduced, and future prospects will be discussed.

Robotic and mechatronic systems are increasingly transitioning from factories to human environments: today we use robots in healthcare, households, and social settings. In these settings, we increasingly see applications that benefit from the physical coupling and interactions between humans and robots. How do we continue to advance the frontiers of these research themes in the “new normal” environment of pandemic lockdowns and remote work? Such circumstances make research advancements challenging, especially for those of us working with experimental hardware that requires human-subjects for validation and verification of our control algorithms. In this talk, I’ll describe my lab’s innovations in simulation-based environments for developing intelligent mechatronic systems that enable pilot testing from anywhere and fast deployment to experimental platforms. I’ll end with a look to the next frontier of assistive robotics, where we are combining a person’s residual capabilities following neurological injury with robotic support to restore their functional independence.

The next generation of robots will soon get out of the secure and predictable environment of factories and will face the complexity and unpredictability of our daily environments. To avoid that robots fail lamely at the task they are programmed to do, robots will need to adapt on the go. I will present techniques from machine learning to allow robots to learn strategies to enable them to react rapidly and efficiently to changes in the environment. Learning the set of feasible solutions will be preferred over learning optimal controllers. I will review methods we have developed to allow instantaneous reactions to perturbation, leveraging on the multiplicity of feasible solutions. I will present applications of these methods for compliant control during human-robot collaborative tasks, safe and reactive navigation when navigating in dense crowds, and for manipulating objects.

The talk is based on the Textbook: Aude Billard, Sina Mirrazavi, & Nadia Figueroa. (2022). Learning for Adaptive and Reactive Robot Control : A Dynamical Systems Approach. The MIT Press.