Touch and deformation perception of soft manipulators with capacitive e-skins and deep learning

Tactile sensing in soft robots remains particularly challenging because of the coupling between contact and deformation information which the sensor is subject to during actuation and interaction with the environment. This often results in severe interference and makes disentangling tactile sensing and geometric deformation difficult. To address this problem, this paper proposes a soft capacitive e-skin with a sparse electrode distribution and deep learning for information decoupling. Our approach successfully separates tactile sensing from geometric deformation, enabling touch recognition on a soft pneumatic actuator subject to both internal (actuation) and external (manual handling) forces. Using a multi-layer perceptron, the proposed e-skin achieves 99.88\% accuracy in touch recognition across a range of deformations. When complemented with prior knowledge, a transformer-based architecture effectively tracks the deformation of the soft actuator. The average distance error in positional reconstruction of the manipulator is as low as 2.905$\pm$2.207 mm, even under operative conditions with different inflation states and physical contacts which lead to additional signal variations and consequently interfere with deformation tracking. These findings represent a tangible way forward in the development of e-skins that can endow soft robots with proprioception and exteroception

A Large Area Tactile Sensor Patch Based on Commercial Force Sensors

This paper reports the design of a tactile sensor patch to cover large areas of robots and machines that interact with human beings. Many devices have been proposed to meet such a demand. These realizations are mostly custom-built or developed in the lab. The sensor of this paper is implemented with commercial force sensors. This has the benefit of a more foreseeable response of the sensor if its behavior is understood as the aggregation of readings from all the individual force sensors in the array. A few reported large area tactile sensors are also based on commercial sensors. However, the one in this paper is the first of this kind based on the use of polymeric commercial force sensing resistors (FSR) as unit elements of the array or tactels, which results in a robust sensor. The paper discusses design issues related to some necessary modifications of the force sensor, its assembly in an array, and the signal conditioning. The patch has 16 × 9 force sensors mounted on a flexible printed circuit board with a spatial resolution of 18.5 mm. The force range of a tactel is 6 N and its sensitivity is 0.6 V/N. The array is read at a rate of 78 frames per second. Finally, two simple application examples are also carried out with the sensor mounted on the forearm of a rescue robot that communicates with the sensor through a CAN bus

Silicone Based Capacitive E-Skin Sensor for Soft Surgical Robots

In this extended abstract, we present a soft stretchable multi-modal capacitive skin sensor that can be used for exteroception and proprioception in soft surgical manipulators. A soft skin prototype was made using Ecoflex, embedding three conductive carbon grease terminal layers. This soft skin is capable of measuring stretch and touch simultaneously. The soft skin measures uniaxial stretches from 1 to 1.2475 within an error range of 2.6% and can also quantify as well as localize local indentation. An algorithm is developed that decouples local change, i.e., due to indentation, from global strain, due to stretch. An experimental study was conducted; results are presented

Design and Development of Sensor Integrated Robotic Hand

Most of the automated systems using robots as agents do use few sensors according to the need. However, there are situations where the tasks carried out by the end-effector, or for that matter by the robot hand needs multiple sensors. The hand, to make the best use of these sensors, and behave autonomously, requires a set of appropriate types of sensors which could be integrated in proper manners. The present research work aims at developing a sensor integrated robot hand that can collect information related to the assigned tasks, assimilate there correctly and then do task action as appropriate. The process of development involves selection of sensors of right types and of right specification, locating then at proper places in the hand, checking their functionality individually and calibrating them for the envisaged process. Since the sensors need to be integrated so that they perform in the desired manner collectively, an integration platform is created using NI PXIe-1082. A set of algorithm is developed for achieving the integrated model. The entire process is first modelled and simulated off line for possible modification in order to ensure that all the sensors do contribute towards the autonomy of the hand for desired activity. This work also involves design of a two-fingered gripper. The design is made in such a way that it is capable of carrying out the desired tasks and can accommodate all the sensors within its fold. The developed sensor integrated hand has been put to work and its performance test has been carried out. This hand can be very useful for part assembly work in industries for any shape of part with a limit on the size of the part in mind. The broad aim is to design, model simulate and develop an advanced robotic hand. Sensors for pick up contacts pressure, force, torque, position, surface profile shape using suitable sensing elements in a robot hand are to be introduced. The hand is a complex structure with large number of degrees of freedom and has multiple sensing capabilities apart from the associated sensing assistance from other organs. The present work is envisaged to add multiple sensors to a two-fingered robotic hand having motion capabilities and constraints similar to the human hand. There has been a good amount of research and development in this field during the last two decades a lot remains to be explored and achieved. The objective of the proposed work is to design, simulate and develop a sensor integrated robotic hand. Its potential applications can be proposed for industrial environments and in healthcare field. The industrial applications include electronic assembly tasks, lighter inspection tasks, etc. Application in healthcare could be in the areas of rehabilitation and assistive techniques. The work also aims to establish the requirement of the robotic hand for the target application areas, to identify the suitable kinds and model of sensors that can be integrated on hand control system. Functioning of motors in the robotic hand and integration of appropriate sensors for the desired motion is explained for the control of the various elements of the hand. Additional sensors, capable of collecting external information and information about the object for manipulation is explored. Processes are designed using various software and hardware tools such as mathematical computation MATLAB, OpenCV library and LabVIEW 2013 DAQ system as applicable, validated theoretically and finally implemented to develop an intelligent robotic hand. The multiple smart sensors are installed on a standard six degree-of-freedom industrial robot KAWASAKI RS06L articulated manipulator, with the two-finger pneumatic SHUNK robotic hand or designed prototype and robot control programs are integrated in such a manner that allows easy application of grasping in an industrial pick-and-place operation where the characteristics of the object can vary or are unknown. The effectiveness of the actual recommended structure is usually proven simply by experiments using calibration involving sensors and manipulator. The dissertation concludes with a summary of the contribution and the scope of further work

Integrated circuit interface for artificial skins

Artificial sensitive skins are intended to emulate the human skin to improve the skills of robots and machinery in complex unstructured environments. They are basically smart arrays of pressure sensors. As in the case of artificial retinas, one problem to solve is the management of the huge amount of information that such arrays provide, especially if this information should be used by a central processing unit to implement some control algorithms. An approach to manage such information is to increment the signal processing performed close to the sensor in order to extract the useful information and reduce the errors caused by long wires. This paper proposes the use of voltage to frequency converters to implement a quite straightforward analog to digital conversion as front end interface to digital circuitry in a smart tactile sensor. The circuitry commonly implemented to read out the information from a piezoresistive tactile sensor can be modified to turn it into an array of voltage to frequency converters. This is carried out in this paper, where the feasibility of the idea is shown through simulations and its performance is discussed.Gobierno de España TEC2006-12376-C02-01, TEC2006-1572

Inertial Parameter Identification Including Friction and Motor Dynamics

Identification of inertial parameters is fundamental for the implementation of torque-based control in humanoids. At the same time, good models of friction and actuator dynamics are critical for the low-level control of joint torques. We propose a novel method to identify inertial, friction and motor parameters in a single procedure. The identification exploits the measurements of the PWM of the DC motors and a 6-axis force/torque sensor mounted inside the kinematic chain. The partial least-square (PLS) method is used to perform the regression. We identified the inertial, friction and motor parameters of the right arm of the iCub humanoid robot. We verified that the identified model can accurately predict the force/torque sensor measurements and the motor voltages. Moreover, we compared the identified parameters against the CAD parameters, in the prediction of the force/torque sensor measurements. Finally, we showed that the estimated model can effectively detect external contacts, comparing it against a tactile-based contact detection. The presented approach offers some advantages with respect to other state-of-the-art methods, because of its completeness (i.e. it identifies inertial, friction and motor parameters) and simplicity (only one data collection, with no particular requirements).Comment: Pre-print of paper presented at Humanoid Robots, 13th IEEE-RAS International Conference on, Atlanta, Georgia, 201

Compliant tactile sensor for generating a signal related to an applied force

Tactile sensor. The sensor includes a compliant convex surface disposed above a sensor array, the sensor array adapted to respond to deformation of the convex surface to generate a signal related to an applied force vector