Haptics Rendering and Applications

There has been significant progress in haptic technologies but the incorporation of haptics into virtual environments is still in its infancy. A wide range of the new society's human activities including communication, education, art, entertainment, commerce and science would forever change if we learned how to capture, manipulate and reproduce haptic sensory stimuli that are nearly indistinguishable from reality. For the field to move forward, many commercial and technological barriers need to be overcome. By rendering how objects feel through haptic technology, we communicate information that might reflect a desire to speak a physically- based language that has never been explored before. Due to constant improvement in haptics technology and increasing levels of research into and development of haptics-related algorithms, protocols and devices, there is a belief that haptics technology has a promising future

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

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

A high speed sensor system for tactile interaction research

Schürmann C. A high speed sensor system for tactile interaction research. Bielefeld: Bielefeld University Library; 2013.In this work we will describe and implement the first tactile sensor system that combines the properties of modularity with a very high sensing speed, a high sensitivity and a high spatial resolution. This unique combination of features enables researchers to develop novel applications and makes it possible to replace task specific tactile sensors with a single system. The very high sensing speed of the system allows for slip detection during robot grasping. And as all our sensor cells are sampled with the same high frequency, our system can even enable the slip detection for multiple contact points at the same time. This high speed was made possible through the development of a highly integrated parallel sensor sampling architecture. The modularity of the system allows it to be employed in a multitude of applications. Tactile sensitive surfaces of various dimensions can be easily realized through a very simple ’plug and use’ principle without the need for software configuration by the user. This was made possible by developing a new bus system that allows the relative localization of the participants. Our system can be used to create tactile sensitive table surfaces with a large amount of sensor cells and due to its high speed design still provide for real time frame rates. The flexibility and high performance of the system enabled us to develop a tactile sensitive object that allows the continuous high speed monitoring of human finger forces. For this we solved the problem of integrating the tactile sensors to allow free movement of the object, while maintaining a constant high rate of data capture and realizing a low latency synchronization to external devices. The high sensitivity of the system was made possible through technical innovation in the state of the art of resistive based tactile sensors. We did so by creating an optimized sensor cell shape and investigating the behavior of different sensor materials. The knowledge gained in this process was further used to advance the existing method of sensor normalization into a real time method. We will present a range of tactile interaction scenarios that have been realized with the tactile sensor system named Myrmex. These scenarios include the investigating of human grasp force control during a pick and place task, a tactile table for integration into an intelligent household and a tactile table for the manipulation of virtual clay as a form of finger training. In addition we will present a selection of scenarios where the Myrmex system was employed by other researchers, as in using the sensor modules as (large) tactile fingertips on robot arms to implement tactile servoing or slip detection during object grasping. The system has also been used to study human finger forces as well as investigating novel methods for prosthesis control. The positive results from all the scenarios support our conclusion that the developed Myrmex system is a very valuable and reliable tool for the research of tactile interactions

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

ISMCR 1994: Topical Workshop on Virtual Reality. Proceedings of the Fourth International Symposium on Measurement and Control in Robotics

This symposium on measurement and control in robotics included sessions on: (1) rendering, including tactile perception and applied virtual reality; (2) applications in simulated medical procedures and telerobotics; (3) tracking sensors in a virtual environment; (4) displays for virtual reality applications; (5) sensory feedback including a virtual environment application with partial gravity simulation; and (6) applications in education, entertainment, technical writing, and animation

Human-Robot Collaborations in Industrial Automation

Technology is changing the manufacturing world. For example, sensors are being used to track inventories from the manufacturing floor up to a retail shelf or a customer’s door. These types of interconnected systems have been called the fourth industrial revolution, also known as Industry 4.0, and are projected to lower manufacturing costs. As industry moves toward these integrated technologies and lower costs, engineers will need to connect these systems via the Internet of Things (IoT). These engineers will also need to design how these connected systems interact with humans. The focus of this Special Issue is the smart sensors used in these human–robot collaborations

Contact sensing--a sequential decision approach to sensing manipulation contact features

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 1995.Includes bibliographical references (p. 179-186).by Brian Scott Eberman.Ph.D

On the Interplay between Mechanical and Computational Intelligence in Robot Hands

Researchers have made tremendous advances in robotic grasping in the past decades. On the hardware side, a lot of robot hand designs were proposed, covering a large spectrum of dexterity (from simple parallel grippers to anthropomorphic hands), actuation (from underactuated to fully actuated), and sensing capabilities (from only open/close states to tactile sensing). On the software side, grasping techniques also evolved significantly, from open-loop control, classical feedback control, to learning-based policies. However, most of the studies and applications follow the one-way paradigm that mechanical engineers/researchers design the hardware first and control/learning experts write the code to use the hand. In contrast, we aim to study the interplay between the mechanical and computational aspects in robotic grasping. We believe both sides are important but cannot solve grasping problems on their own, and both sides are highly connected by the laws of physics and should not be developed separately. We use the term "Mechanical Intelligence" to refer to the ability realized by mechanisms to appropriately respond to the external inputs, and we show that incorporating Mechanical Intelligence with Computational Intelligence is beneficial for grasping. The first part of this thesis is to derive hand underactuation mechanisms from grasp data. The mechanical coordination in robot hands, which is one type of Mechanical Intelligence, corresponds to the concept of dimensionality reduction in Machine Learning. However, the resulted low-dimensional manifolds need to be realizable using underactuated mechanisms. In this project, we first collect simulated grasp data without accounting for underactuation, apply a dimensionality reduction technique (we term it "Mechanically Realizable Manifolds") considering both pre-contact postural synergies and post-contact joint torque coordination, and finally build robot hands based on the resulted low-dimensional models. We also demonstrate a real-world application on a free-flying robot for the International Space Station. The second part is about proprioceptive grasping for unknown objects by taking advantage of hand compliance. Mechanical compliance is intrinsically connected to force/torque sensing and control. In this work, we proposed a series-elastic hand providing embodied compliance and proprioception, and an associated grasping policy using a network of proportional-integral controllers. We show that, without any prior model of the object and with only proprioceptive sensing, a robot hand can make stable grasps in a reactive fashion. The last part is about developing the Mechanical and Computational Intelligence jointly --- to co-optimize the mechanisms and control policies using deep Reinforcement Learning (RL). Traditional RL treats robot hardware as immutable and models it as part of the environment. In contrast, we move the robot hardware out of the environment, express its mechanics as auto-differentiable physics and connect it with the computational policy to create a unified policy (we term this method "Hardware as Policy"), which allows RL algorithms to back-propagate gradients w.r.t both hardware and computational parameters and optimize them in the same fashion. We present a mass-spring toy problem to illustrate this idea, and also a real-world design case of an underactuated hand. The three projects we present in this thesis are meaningful examples to demonstrate the interplay between the mechanical and computational aspects of robotic grasping. In the Conclusion part, we summarize some high-level philosophies and suggestions to integrate Mechanical and Computational Intelligence, as well as the high-level challenges that still exist when pushing this area forward