Semi-autonomous scheme for pushing micro-objects

-In many microassembly applications, it is often desirable to position and orient polygonal micro-objects lying on a planar surface. Pushing micro-objects using point contact provides more flexibility and less complexity compared to pick and place operation. Due to the fact that in micro-world surface forces are much more dominant than inertial forces and these forces are distributed unevenly, pushing through the center of mass of the micro-object will not yield a pure translational motion. In order to translate a micro-object, the line of pushing should pass through the center of friction. In this paper, a semi-autonomous scheme based on hybrid vision/force feedback is proposed to push microobjects with human assistance using a custom built telemicromanipulation setup to achieve pure translational motion. The pushing operation is divided into two concurrent processes: In one process human operator who acts as an impedance controller alters the velocity of the pusher while in contact with the micro-object through scaled bilateral teleoperation with force feedback. In the other process, the desired line of pushing for the micro-object is determined continuously using visual feedback procedures so that it always passes through the varying center of friction. Experimental results are demonstrated to prove nanoNewton range force sensing, scaled bilateral teleoperation with force feedback and pushing microobjects

Leg Coordination during Walking in Insects

Locomotion depends on constant adaptation to different requirements of the environment. An appropriate temporal and spatial coordination of multiple body parts is necessary to achieve a stable and adapted behavior. Until now it is unclear how the neuronal structures can achieve these meaningful adaptations. The exact role of the nervous system, muscles and mechanical constrains are not known. By using preparations in which special forms of adaptations are considered under experimental conditions that selectively exclude external influences, like mechanical interactions through the ground or differences in body mass, one can draw conclusions about the organization of the respective underlying neuronal structures. In the present thesis, four different publications are presented, giving evidence of mechanisms of temporal or spatial coordination of leg movements in the stick insect Carausius morosus and the fruit fly Drosophila melanogaster during different experimental paradigms. At first, state dependent local coordinating mechanisms are analyzed. Electromyographic measurements of the three major antagonistic leg muscle pairs of the forward and backward walking stick insect are evaluated. It becomes evident that only the motor activity of the most proximal leg joint is changed when walking direction is changed from forward to backward, which demonstrates that the neuronal networks driving movement in each individual leg seem to be organized in a modular structure. In the second part mechanisms that influence movement speed of the individual leg and coordination of speed between the different legs of the stick insect come into focus. Electrophysiological and behavioral experiments with the intact and reduced stick insect were used to examine relationships between the velocity of a stepping front leg and neuronal activity in the mesothoracic segment as well as correlations between the stepping velocities of different legs during walks with constant velocity or with distinct accelerations. It was shown that stepping velocity of single legs were not reflected in motoneuron activity or stepping velocity of another leg. Only when an increase in walking speed was induced, clear correlation in the stepping velocities of the individual legs was found. Subsequently, the analysis of changes in temporal leg coordination during different walking speeds in the fruit fly reveals that the locomotor system of Drosophila can cover a broad range of walking speeds and seems to follow the same rules as the locomotor system of the stick insect. Walking speed is increased by modifying stance duration, whereas swing duration and step amplitude remain largely unchanged. Changes in inter-leg coordination are gradually and systematically with walking speed and can adapt to major biomechanical changes in its walking apparatus. In the final part it was the aim to understand the role of neuronal mechanisms for the orientation and spatial coordination of foot placement in the stick insect. Placement of middle and hind legs with respect to the position of their respective rostrally neighboring leg were analyzed under two different conditions. Segment and state dependent differences in the aiming accuracy of the middle and hind legs could be shown, which indicate differences in the underlying neuronal structures in the different segments and the importance of movement in the target leg for the processing of the position information. Taken together, common principles in inter-leg coordination where found, like similarities between different organisms and segment specific or state dependent modifications in the walking system. They can be interpreted as evidence for a highly adaptive and modular design of the underlying neuronal structures

Design, evaluation, and control of nexus: a multiscale additive manufacturing platform with integrated 3D printing and robotic assembly.

Additive manufacturing (AM) technology is an emerging approach to creating three-dimensional (3D) objects and has seen numerous applications in medical implants, transportation, aerospace, energy, consumer products, etc. Compared with manufacturing by forming and machining, additive manufacturing techniques provide more rapid, economical, efficient, reliable, and complex manufacturing processes. However, additive manufacturing also has limitations on print strength and dimensional tolerance, while traditional additive manufacturing hardware platforms for 3D printing have limited flexibility. In particular, part geometry and materials are limited to most 3D printing hardware. In addition, for multiscale and complex products, samples must be printed, fabricated, and transferred among different additive manufacturing platforms in different locations, which leads to high cost, long process time, and low yield of products. This thesis investigates methods to design, evaluate, and control the NeXus, which is a novel custom robotic platform for multiscale additive manufacturing with integrated 3D printing and robotic assembly. NeXus can be used to prototype miniature devices and systems, such as wearable MEMS sensor fabrics, microrobots for wafer-scale microfactories, tactile robot skins, next generation energy storage (solar cells), nanostructure plasmonic devices, and biosensors. The NeXus has the flexibility to fixture, position, transport, and assemble components across a wide spectrum of length scales (Macro-Meso-Micro-Nano, 1m to 100nm) and provides unparalleled additive process capabilities such as 3D printing through both aerosol jetting and ultrasonic bonding and forming, thin-film photonic sintering, fiber loom weaving, and in-situ Micro-Electro-Mechanical System (MEMS) packaging and interconnect formation. The NeXus system has a footprint of around 4m x 3.5m x 2.4m (X-Y-Z) and includes two industrial robotic arms, precision positioners, multiple manipulation tools, and additive manufacturing processes and packaging capabilities. The design of the NeXus platform adopted the Lean Robotic Micromanufacturing (LRM) design principles and simulation tools to mitigate development risks. The NeXus has more than 50 degrees of freedom (DOF) from different instruments, precise evaluation of the custom robots and positioners is indispensable before employing them in complex and multiscale applications. The integration and control of multi-functional instruments is also a challenge in the NeXus system due to different communication protocols and compatibility. Thus, the NeXus system is controlled by National Instruments (NI) LabVIEW real-time operating system (RTOS) with NI PXI controller and a LabVIEW State Machine User Interface (SMUI) and was programmed considering the synchronization of various instruments and sequencing of additive manufacturing processes for different tasks. The operation sequences of each robot along with relevant tools must be organized in safe mode to avoid crashes and damage to tools during robots’ motions. This thesis also describes two demonstrators that are realized by the NeXus system in detail: skin tactile sensor arrays and electronic textiles. The fabrication process of the skin tactile sensor uses the automated manufacturing line in the NeXus with pattern design, precise calibration, synchronization of an Aerosol Jet printer, and a custom positioner. The fabrication process for electronic textiles is a combination of MEMS fabrication techniques in the cleanroom and the collaboration of multiple NeXus robots including two industrial robotic arms and a custom high-precision positioner for the deterministic alignment process

History information emerges in the cortex during learning

We learn from our experience but the underlying neuronal mechanisms incorporating past information to facilitate learning is relatively unknown. Specifically, which cortical areas encode history-related information and how is this information modulated across learning? To study the relationship between history and learning, we continuously imaged cortex-wide calcium dynamics as mice learn to use their whiskers to discriminate between two different textures. We mainly focused on comparing the same trial type with different trial history, that is, a different preceding trial. We found trial history information in barrel cortex (BC) during stimulus presentation. Importantly, trial history in BC emerged only as the mouse learned the task. Next, we also found learning-dependent trial history information in rostrolateral (RL) association cortex that emerges before stimulus presentation, preceding activity in BC. Trial history was also encoded in other cortical areas and was not related to differences in body movements. Interestingly, a binary classifier could discriminate trial history at the single trial level just as well as current information both in BC and RL. These findings suggest that past experience emerges in the cortex around the time of learning, starting from higher-order association area RL and propagating down (i.e., top-down projection) to lower-order BC where it can be integrated with incoming sensory information. This integration between the past and present may facilitate learning