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

Tactile Sensors Based on Conductive Polymers

This paper presents results from a selection of tactile sensors that have been designed and fabricated. These sensors are based on a common approach that consists in placing a sheet of piezoresistive material on the top of a set of electrodes. We use a thin film of conductive polymer as the piezoresistive mate¬rial. Specifically, a conductive water-based ink of this polymer is deposited by spin coating on a flexible plastic sheet, giving it a smooth, homogeneous and conducting thin film. The main interest in this procedure is that it is cheap and it allows the fabrication of flexible and low cost tactile sensors. In this work we present results from sensors made using two technologies. Firstly, we have used a flexible Printed Circuit Board (PCB) technology to fabricate the set of electrodes and addressing tracks. The result is a simple, flexible tactile sensor. In addition to these sensors on PCB, we have proposed, designed and fabricated sensors with screen printing technology. In this case, the set of electrodes and addressing tracks are made by printing an ink based on silver nanoparticles. The intense characterization provides us insights into the design of these tactile sensors.This work has been partially funded by the spanish government under contract TEC2006-12376-C02

Improved Normal and Shear Tactile Force Sensor Performance via Least Squares Artificial Neural Network (LSANN)

This paper presents a new approach to the characterization of tactile array sensors that aims to reduce the computational time needed for convergence to obtain a useful estimator for normal and shear forces. This is achieved by breaking up the sensor characterization into two parts: a linear regression portion using multivariate least squares regression, and a nonlinear regression portion using a neural network as a multi-input, multi-output function approximator. This procedure has been termed Least Squares Artificial Neural Network (LSANN). By applying LSANN on the 2nd generation MIT Cheetah footpad, the convergence speed for the estimator of the normal and shear forces is improved by 59.2% compared to using only the neural network alone. The normalized root mean squared error between the two methods are nearly identical at 1.17% in the normal direction, and 8.30% and 10.14% in the shear directions. This approach could have broader implications in greatly reducing the amount of time needed to train a contact force estimator for a large number of tactile sensor arrays (i.e. in robotic hands and skin).United States. Defense Advanced Research Projects Agency. Maximum Mobility and Manipulation (M3) programSingapore. Agency for Science, Technology and Researc

Assessment of eggplant firmness with accelerometers on a pneumatic robot gripper

A pneumatic robot gripper capable of sorting eggplants according to their firmness has been developed and tested. The gripper has three fingers and one suction cup. Each finger has an inertial sensor attached to it. One of the fingers adapts to and copies the shapes of eggplants when the jamming of its internal granular material changes from soft to hard. The other fingers adapt to the shape of the eggplant with the use of extra degrees of freedom. Specific software acquires and processes the information obtained with the inertial sensors and generates 16 independent variables extracted from the signals. A total of 234 eggplants were selected and tested on the same day with the robot gripper, during the pick-and-place operation, and with a destructive firmness tester. The non-destructive parameters extracted from the gripper finger accelerometers were used to build and validate a partial least square model, with a calibration regression coefficient of r = 0.87 and a high prediction performance (r = 0.90). Furthermore, from the results of the paper, it has been seen that the procedure can be simplified by using only two non-destructive impacts and one uniaxial accelerometer to assess eggplant firmness. The non-destructive assessment of firmness while grasping agricultural products in pick-and-place operations could be implemented in many prehensile pneumatic robot grippers. This technique could mean an important advance in the hygienic postharvest handling of fruits and vegetables.This research is supported by MANI-DACSA project (Ref. RTA2012-00062-C04-02), partially funded by the Spanish Government (Ministerio de Economia y Competitividad).Blanes Campos, C.; Ortiz Sánchez, MC.; Mellado Arteche, M.; Beltrán Beltrán, P. (2015). Assessment of eggplant firmness with accelerometers on a pneumatic robot gripper. Computers and Electronics in Agriculture. 113:44-50. https://doi.org/10.1016/j.compag.2015.01.013S445011

Issues in Vision, Semi-autonomous Control, Haptics and Manipulation in Robotics for Nuclear Decommissioning

Traditionally, the nuclear industry has preferred the use of tele-operated control within robotic applications such as decommissioning. This is due to obvious safety reasons, along with other less apparent motivations such as the safeguarding of industry jobs, and a lack of coding expertise in the industry. However, problems with the use of such techniques have been evident within the past few years, mostly associated with operator fatigue leading to errors. A typical modern autonomous robotic system will utilise some sort of stereoscopic 3D vision system (often based on LIDAR) to aid recognition. However, this information can be hard to relay to a human tele-operator not used to such information. Further, tele-operation of a modern robot is a truly complex and specialised skill, and there are a lack of people with in the nuclear industry (and indeed industry as a whole) with these skills. A potential solution to alleviate these problems may be in the use of semi-autonomous control where the robotic artificial intelligence may be used for low-level tasks while the human operator would handle the higher-level decisions. Instead of the operator having to directly control the robot via two joysticks, the operator would be more likely to be confronted with a large touchscreen complete with a list of tasks and highlighted objects on which the robot can perform them upon

Robust dexterous telemanipulation following object-orientation commands

This paper aims to present a procedure to change the orientation of a grasped object using dexterous manipulation. The manipulation is controlled by teleoperation in a very simple way, with the commands introduced by an operator using a keyboard. Design/methodology/approach - The paper shows a teleoperation scheme, hand kinematics and a manipulation strategy to manipulate different objects using the Schunk Dexterous Hand (SDH2). A state machine is used to model the teleoperation actions and the system states. A virtual link is used to include the contact point on the hand kinematics of the SDH2. Findings - Experiments were conducted to evaluate the proposed approach with different objects, varying the initial grasp configuration and the sequence of actions commanded by the operator. Originality/value - The proposed approach uses a shared telemanipulation schema to perform dexterous manipulation; in this schema, the operator sends high-level commands and a local system uses this information, jointly with tactile measurements and the current status of the system, to generate proper setpoints for the low-level control of the fingers, which may be a commercial close one. The main contribution of this work is the mentioned local system, simple enough for practical applications and robust enough to avoid object falls.Postprint (author's final draft

Robust dexterous telemanipulation following object-orientation commands

This paper aims to present a procedure to change the orientation of a grasped object using dexterous manipulation. The manipulation is controlled by teleoperation in a very simple way, with the commands introduced by an operator using a keyboard. Design/methodology/approach - The paper shows a teleoperation scheme, hand kinematics and a manipulation strategy to manipulate different objects using the Schunk Dexterous Hand (SDH2). A state machine is used to model the teleoperation actions and the system states. A virtual link is used to include the contact point on the hand kinematics of the SDH2. Findings - Experiments were conducted to evaluate the proposed approach with different objects, varying the initial grasp configuration and the sequence of actions commanded by the operator. Originality/value - The proposed approach uses a shared telemanipulation schema to perform dexterous manipulation; in this schema, the operator sends high-level commands and a local system uses this information, jointly with tactile measurements and the current status of the system, to generate proper setpoints for the low-level control of the fingers, which may be a commercial close one. The main contribution of this work is the mentioned local system, simple enough for practical applications and robust enough to avoid object falls.Postprint (author's final draft