Fluid‐driven soft CoboSkin for safer human–robot collaboration: fabrication and adaptation

In human–robot collaboration, the wrapping material on robots is not only required to have the sensing ability to adapt to the external environment but also need to have the function of cushioning the collision between human and robot. Herein, a fluid‐driven soft robot skin with sensing and actuating function is successfully applied to a collaborative robot and working well with the host robot. The skin is an integration of sponge force sensors and pneumatic actuators. By altering the internal air pressure in pneumatic actuators, the developed robot skin can provide more than ten times tunable stiffness and sensitivity. In addition, the skin can reduce the peak force of the collision and achieve the actuating function. Using three‐dimensional printing and computer‐aided design, the skin is fabricated and attached to a collaborative robot conformally. Drawing upon the data acquisition and control system, the experiment for illustrating the applications of the CoboSkin is successfully performed. The skin provides the robot with multi‐functions, which are similar to the human muscle and skin attached to human bones. By mimicking human skin and muscle with tactile sensing function and stiffness tuning function, CoboSkin can enhance the adaptability of the robot to human daily life

Material perception and action : The role of material properties in object handling

This dissertation is about visual perception of material properties and their role in preparation for object handling. Usually before an object is touched or picked-up we estimate its size and shape based on visual features to plan the grip size of our hand. After we have touched the object, the grip size is adjusted according to the provided haptic feedback and the object is handled safely. Similarly, we anticipate the required grip force to handle the object without slippage, based on its visual features and prior experience with similar objects. Previous studies on object handling have mostly examined object characteristics that are typical for object recognition, e.g., size, shape, weight, but in the recent years there has been a growing interest in object characteristics that are more typical to the type of material the object is made from. That said, in a series of studies we investigated the role of perceived material properties in decision-making and object handling, in which both digitally rendered materials and real objects made of different types of materials were presented to human subjects and a humanoid robot. Paper I is a reach-to-grasp study where human subjects were examined using motion capture technology. In this study, participants grasped and lifted paper cups that varied in appearance (i.e., matte vs. glossy) and weight. Here we were interested in both the temporal and spatial components of prehension to examine the role of material properties in grip preparation, and how visual features contribute to inferred hardness before haptic feedback has become available. We found the temporal and spatial components were not exclusively governed by the expected weight of the paper cups, instead glossiness and expected hardness has a significant role as well. In paper II, which is a follow-up on Paper I, we investigated the grip force component of prehension using the same experimental stimuli as used in paper I. In a similar experimental set up, using force sensors we examined the early grip force magnitudes applied by human subjects when grasping and lifting the same paper cups as used in Paper I. Here we found that early grip force scaling was not only guided by the object weight, but the visual characteristics of the material (i.e., matte vs. glossy) had a role as well. Moreover, the results suggest that grip force scaling during the initial object lifts is guided by expected hardness that is to some extend based on visual material properties. Paper III is a visual judgment task where psychophysical measurements were used to examine how the material properties, roughness and glossiness, influence perceived bounce height and consequently perceived hardness. In a paired-comparison task, human subjects observed a bouncing ball bounce on various surface planes and judged their bounce height. Here we investigated, what combination of surface properties, i.e., roughness or glossiness, makes a surface plane to be perceived bounceable. The results demonstrate that surface planes with rough properties are believed to afford higher bounce heights for the bouncing ball, compared to surface planes with smooth properties. Interestingly, adding shiny properties to the rough and smooth surface planes, reduced the judged difference, as if surface planes with gloss are believed to afford higher bounce heights irrespective of how smooth or rough the surface plane is beneath. This suggests that perceived bounce height involves not only the physical elements of the bounce height, but also the visual characteristics of the material properties of the surface planes the ball bounces on. In paper IV we investigated the development of material knowledge using a robotic system. A humanoid robot explored real objects made of different types of materials, using both camera and haptic systems. The objects varied in visual appearances (e.g., texture, color, shape, size), weight, and hardness, and in two experiments, the robot picked up and placed the experimental objects several times using its arm. Here we used the haptic signals from the servos controlling the arm and the shoulder of the robot, to obtain measurements of the weight and hardness of the objects, and the camera system to collect data on the visual features of the objects. After the robot had repeatedly explored the objects, an associative learning model was created based on the training data to demonstrate how the robotic system could produce multi-modal mapping between the visual and haptic features of the objects. In sum, in this thesis we show that visual material properties and prior knowledge of how materials look like and behave like has a significant role in action planning

Flexible Electronics for Neurological Electronic Skin with Multiple Sensing Modalities

The evolution of electronic skin (E-skin) technology in the past decade has resulted in a great variety of flexible electronic devices that mimic the physical and chemical sensing properties of skin for applications in advanced robotics, prosthetics, and health monitoring technologies. The further advancement of E-skin technology demands closer imitation of skin receptors\u27 transduction mechanisms, simultaneous detection of multiple information from different sources, and the study of transmission, processing and memory of the signals among the neurons. Motivated by such demands, this thesis focuses on design, fabrication, characterization of novel flexible electronic devices and integration of individual devices to realize prototype biomimetic E-skin with neurological and multimodal sensing functions. More specifically, we have studied flexible carbon nanotube thin-film transistors (CNT-TFTs) as control and signal processing units of E-skin and flexible ferroelectret nanogenerator (FENG) and triboelectric nanogenerator (TENG) as skin mechanoreceptors. Multiple fabrication methods, such as low-cost printing and conventional cleanroom-based microfabrication have been implemented to fabricate flexible CNT-TFTs with different structures and functions, especially the synaptic functions. Based on the research on individual devices, we have demonstrated a prototype force-sensing flexible neurological E-skin and its sensory nerve and synapse, with FENG serving as the sensory mechanoreceptor that generates action potentials (pulsed voltages) to be processed and transmitted by the flexible synaptic CNT-TFT. It allows for instantaneous detection of force stimuli and offers biological synapse-like behavior to store the stimulus information and relay the stimulus signals to the next stage. The force-sensing neurological E-skin was further augmented with visual and auditory sensing modalities by introducing phototransistor-based optical sensor and FENG-based acoustic sensor. Successful transduction of visual, auditory and tactile stimuli and synaptic processing and memory of those signals have all been demonstrated. Thanks to the multimodal sensing capability of the neurological E-skin, psychological associative learning experiment-“Pavlov’s dog\u27s experiment”, was also successfully implemented electronically by synergizing actual visual and auditory signals in the synaptic transistor. Flexible electronics and prototype neurological E-skin system demonstrated in this thesis may offer an entry into novel multimodal, user-environment interactive soft E-skin system for soft robotic and diagnostic applications

Haptics: Science, Technology, Applications

This open access book constitutes the proceedings of the 12th International Conference on Human Haptic Sensing and Touch Enabled Computer Applications, EuroHaptics 2020, held in Leiden, The Netherlands, in September 2020. The 60 papers presented in this volume were carefully reviewed and selected from 111 submissions. The were organized in topical sections on haptic science, haptic technology, and haptic applications. This year's focus is on accessibility

Haptics: Science, Technology, Applications

This open access book constitutes the proceedings of the 13th International Conference on Human Haptic Sensing and Touch Enabled Computer Applications, EuroHaptics 2022, held in Hamburg, Germany, in May 2022. The 36 regular papers included in this book were carefully reviewed and selected from 129 submissions. They were organized in topical sections as follows: haptic science; haptic technology; and haptic applications

Development of Multifunctional E-skin Sensors

Electronic skin (e-skin) is a hot topic due to its enormous potential for health monitoring, functional prosthesis, robotics, and human-machine-interfaces (HMI). For these applications, pressure and temperature sensors and energy harvesters are essential. Their performance may be tuned by their films micro-structuring, either through expensive and time-consuming photolithography techniques or low-cost yet low-tunability approaches. This PhD thesis aimed to introduce and explore a new micro-structuring technique to the field of e-skin – laser engraving – to produce multifunctional e-skin devices able to sense pressure and temperature while being self-powered. This technique was employed to produce moulds for soft lithography, in a low-cost, fast, and highly customizable way. Several parameters of the technique were studied to evaluate their impact in the performance of the devices, such as moulds materials, laser power and speed, and design variables. Amongst the piezoresistive sensors produced, sensors suitable for blood pressure wave detection at the wrist [sensitivity of – 3.2 kPa-1 below 119 Pa, limit of detection (LOD) of 15 Pa], general health monitoring (sensitivity of 4.5 kPa-1 below 10 kPa, relaxation time of 1.4 ms, micro-structured film thickness of only 133 µm), and robotics and functional prosthesis (sensitivity of – 6.4 × 10-3 kPa-1 between 1.2 kPa and 100 kPa, stable output over 27 500 cycles) were obtained. Temperature sensors with micro-cones were achieved with a temperature coefficient of resistance (TCR) of 2.3 %/°C. Energy harvesters based on micro-structured composites of polydimethylsiloxane (PDMS) and zinc tin oxide (ZnSnO3) nanowires (NWs; 120 V and 13 µA at > 100 N) or zinc oxide (ZnO) nanorods (NRs; 6 V at 2.3 N) were produced as well. The work described herein unveils the tremendous potential of the laser engraving technique to produce different e-skin devices with adjustable performance to suit distinct applications, with a high benefit/cost ratio