Modeling, simulation and control of microrobots for the microfactory.

Future assembly technologies will involve higher levels of automation in order to satisfy increased microscale or nanoscale precision requirements. Traditionally, assembly using a top-down robotic approach has been well-studied and applied to the microelectronics and MEMS industries, but less so in nanotechnology. With the boom of nanotechnology since the 1990s, newly designed products with new materials, coatings, and nanoparticles are gradually entering everyone’s lives, while the industry has grown into a billion-dollar volume worldwide. Traditionally, nanotechnology products are assembled using bottom-up methods, such as self-assembly, rather than top-down robotic assembly. This is due to considerations of volume handling of large quantities of components, and the high cost associated with top-down manipulation requiring precision. However, bottom-up manufacturing methods have certain limitations, such as components needing to have predefined shapes and surface coatings, and the number of assembly components being limited to very few. For example, in the case of self-assembly of nano-cubes with an origami design, post-assembly manipulation of cubes in large quantities and cost-efficiency is still challenging. In this thesis, we envision a new paradigm for nanoscale assembly, realized with the help of a wafer-scale microfactory containing large numbers of MEMS microrobots. These robots will work together to enhance the throughput of the factory, while their cost will be reduced when compared to conventional nanopositioners. To fulfill the microfactory vision, numerous challenges related to design, power, control, and nanoscale task completion by these microrobots must be overcome. In this work, we study two classes of microrobots for the microfactory: stationary microrobots and mobile microrobots. For the stationary microrobots in our microfactory application, we have designed and modeled two different types of microrobots, the AFAM (Articulated Four Axes Microrobot) and the SolarPede. The AFAM is a millimeter-size robotic arm working as a nanomanipulator for nanoparticles with four degrees of freedom, while the SolarPede is a light-powered centimeter-size robotic conveyor in the microfactory. For mobile microrobots, we have introduced the world’s first laser-driven micrometer-size locomotor in dry environments, called ChevBot to prove the concept of the motion mechanism. The ChevBot is fabricated using MEMS technology in the cleanroom, following a microassembly step. We showed that it can perform locomotion with pulsed laser energy on a dry surface. Based on the knowledge gained with the ChevBot, we refined tits fabrication process to remove the assembly step and increase its reliability. We designed and fabricated a steerable microrobot, the SerpenBot, in order to achieve controllable behavior with the guidance of a laser beam. Through modeling and experimental study of the characteristics of this type of microrobot, we proposed and validated a new type of deep learning controller, the PID-Bayes neural network controller. The experiments showed that the SerpenBot can achieve closed-loop autonomous operation on a dry substrate

Contact aware robust semi-autonomous teleoperation of mobile manipulators

In the context of human-robot collaboration, cooperation and teaming, the use of mobile manipulators is widespread on applications involving unpredictable or hazardous environments for humans operators, like space operations, waste management and search and rescue on disaster scenarios. Applications where the manipulator's motion is controlled remotely by specialized operators. Teleoperation of manipulators is not a straightforward task, and in many practical cases represent a common source of failures. Common issues during the remote control of manipulators are: increasing control complexity with respect the mechanical degrees of freedom; inadequate or incomplete feedback to the user (i.e. limited visualization or knowledge of the environment); predefined motion directives may be incompatible with constraints or obstacles imposed by the environment. In the latter case, part of the manipulator may get trapped or blocked by some obstacle in the environment, failure that cannot be easily detected, isolated nor counteracted remotely. While control complexity can be reduced by the introduction of motion directives or by abstraction of the robot motion, the real-time constraint of the teleoperation task requires the transfer of the least possible amount of data over the system's network, thus limiting the number of physical sensors that can be used to model the environment. Therefore, it is of fundamental to define alternative perceptive strategies to accurately characterize different interaction with the environment without relying on specific sensory technologies. In this work, we present a novel approach for safe teleoperation, that takes advantage of model based proprioceptive measurement of the robot dynamics to robustly identify unexpected collisions or contact events with the environment. Each identified collision is translated on-the-fly into a set of local motion constraints, allowing the exploitation of the system redundancies for the computation of intelligent control laws for automatic reaction, without requiring human intervention and minimizing the disturbance of the task execution (or, equivalently, the operator efforts). More precisely, the described system consist in two different building blocks. The first, for detecting unexpected interactions with the environment (perceptive block). The second, for intelligent and autonomous reaction after the stimulus (control block). The perceptive block is responsible of the contact event identification. In short, the approach is based on the claim that a sensorless collision detection method for robot manipulators can be extended to the field of mobile manipulators, by embedding it within a statistical learning framework. The control deals with the intelligent and autonomous reaction after the contact or impact with the environment occurs, and consist on an motion abstraction controller with a prioritized set of constrains, where the highest priority correspond to the robot reconfiguration after a collision is detected; when all related dynamical effects have been compensated, the controller switch again to the basic control mode

Design, fabrication and control of soft robots

Conventionally, engineers have employed rigid materials to fabricate precise, predictable robotic systems, which are easily modelled as rigid members connected at discrete joints. Natural systems, however, often match or exceed the performance of robotic systems with deformable bodies. Cephalopods, for example, achieve amazing feats of manipulation and locomotion without a skeleton; even vertebrates such as humans achieve dynamic gaits by storing elastic energy in their compliant bones and soft tissues. Inspired by nature, engineers have begun to explore the design and control of soft-bodied robots composed of compliant materials. This Review discusses recent developments in the emerging field of soft robotics.National Science Foundation (U.S.) (Grant IIS-1226883

Robot Manipulators

Robot manipulators are developing more in the direction of industrial robots than of human workers. Recently, the applications of robot manipulators are spreading their focus, for example Da Vinci as a medical robot, ASIMO as a humanoid robot and so on. There are many research topics within the field of robot manipulators, e.g. motion planning, cooperation with a human, and fusion with external sensors like vision, haptic and force, etc. Moreover, these include both technical problems in the industry and theoretical problems in the academic fields. This book is a collection of papers presenting the latest research issues from around the world

Human-like arm motion generation: a review

In the last decade, the objectives outlined by the needs of personal robotics have led to the rise of new biologically-inspired techniques for arm motion planning. This paper presents a literature review of the most recent research on the generation of human-like arm movements in humanoid and manipulation robotic systems. Search methods and inclusion criteria are described. The studies are analyzed taking into consideration the sources of publication, the experimental settings, the type of movements, the technical approach, and the human motor principles that have been used to inspire and assess human-likeness. Results show that there is a strong focus on the generation of single-arm reaching movements and biomimetic-based methods. However, there has been poor attention to manipulation, obstacle-avoidance mechanisms, and dual-arm motion generation. For these reasons, human-like arm motion generation may not fully respect human behavioral and neurological key features and may result restricted to specific tasks of human-robot interaction. Limitations and challenges are discussed to provide meaningful directions for future investigations.FCT Project UID/MAT/00013/2013FCT–Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020

Development of a Robotic Positioning and Tracking System for a Research Laboratory

Measurement of residual stress using neutron or synchrotron diffraction relies on the accurate alignment of the sample in relation to the gauge volume of the instrument. Automatic sample alignment can be achieved using kinematic models of the positioning system provided the relevant kinematic parameters are known, or can be determined, to a suitable accuracy. The main problem addressed in this thesis is improving the repeatability and accuracy of the sample positioning for the strain scanning, through the use of techniques from robotic calibration theory to generate kinematic models of both off-the-shelf and custom-built positioning systems. The approach is illustrated using a positioning system in use on the ENGIN-X instrument at the UK’s ISIS pulsed neutron source comprising a traditional XYZΩ table augmented with a triple axis manipulator. Accuracies better than 100microns were achieved for this compound system. Although discussed here in terms of sample positioning systems these methods are entirely applicable to other moving instrument components such as beam shaping jaws and detectors. Several factors could lead to inaccurate positioning on a neutron or synchrotron diffractometer. It is therefore essential to validate the accuracy of positioning especially during experiments which require a high level of accuracy. In this thesis, a stereo camera system is developed to monitor the sample and other moving parts of the diffractometer. The camera metrology system is designed to measure the positions of retroreflective markers attached to any object that is being monitored. A fully automated camera calibration procedure is developed with an emphasis on accuracy. The potential accuracy of this system is demonstrated and problems that limit accuracy are discussed. It is anticipated that the camera system would be used to correct the positioning system when the error is minimal or notify the user of the error when it is significant