Raul Fernandez

Micro-Vibration-Based Slip Detection in Tactile Force Sensors

Tactile sensing provides critical information, such as force, texture, shape or temperature, in manipulation tasks. In particular, tactile sensors traditionally used in robotics are emphasized in contact force determination for grasping control and object recognition. Nevertheless, slip detection is also crucial to successfully manipulate an object. Several approaches have appeared to detect slipping, the majority being a combination of complex sensors with complex algorithms. In this paper, we deal with simplicity, analyzing how a novel, but simple, algorithm, based on micro-vibration detection, can be used in a simple, but low-cost and durable, force sensor. We also analyze the results of using the same principle to detect slipping in other force sensors based on flexible parts. In particular, we show and compare the slip detection with: (i) a flexible finger, designed by the authors, acting as a force sensor; (ii) the finger torque sensor of a commercial robotic hand; (iii) a commercial six-axis force sensor mounted on the wrist of a robot; and (iv) a fingertip piezoresistive matrix sensor.

A wall climbing robot for tank inspection. An autonomous prototype

This paper describes a solution to a mobile climbing robot on magnetic wheels, designed for inspecting exterior oil tank surfaces made of metal sheets. A mechanical design has been developed which presents a practical solution without an umbilical cord. The inspection system has been developed based on client/server architecture. The robot runs a client application and a remote PC executes the server functions. They will both allow any necessary inspections to be performed simultaneously by more than one robot. A sensorial system and a data fusion strategy to estimate the absolute robot position is proposed to allow the robot to navigate autonomously. The graphical monitoring of the robot position in the remote PC (server application) provides the operator with the possibility of controlling the robot, even in situations in which the operator visibility of an area tank is very low or inexistent. Previous experiments have demonstrated the mechanical systems robustness. These experiments consist of robot trajectory measurements and the comparison to a motion kinematic model.

Design parameters of flexible grippers for grasping

Flexible-finger hands/grippers have some advantages over rigid ones when used in grasping tasks. For example, they absorb energy during the impact, which make them suitable in delicate manipulation or human interaction. In this work, we look at their performance during grasping tasks, analyzing the effect of some design parameters like precurvature and stiffness of the links, number/DOFs of fingers or scale of the hand. Our work is based on a grasp stability analysis together with a grasp closure analysis adapted to flexible hands. Simulation and experimental tests with a two flexible-finger gripper are provided as validation of our analysis.

Slip Detection in a Novel Tactile Force Sensor

Tactile sensing improves the manipulation and grasping of unknown objects. It contributes to increase the knowledge of the environment and provides useful information to improve grasping control. The sensors traditionally used for tactile sensing emphasize in grasping object shape and force detection. However slip detection is also crucial to successfully manipulate an object. Several approaches have appeared to detect slipping, the majority being a combination of complex sensors with complex algorithms. In this paper, we present a simple, low cost and durable tactile force sensor and its use to slip detection via a simple but effective method based on micro-vibration detection. We also analyze the results of using the same principle to detect slip in other force sensors based on flexible parts. In particular, we also show the slip detection with: a flexible finger (designed by the authors) acting as a force sensor, the finger torque sensor of a commercial robotic hand (Barrett Hand), and a commercial 6-axis force sensor mounted in the wrist of a robot.

In-hand object localization: Simple vs. complex tactile sensors

How good is a tactile sensor for tactile exploration and in-hand object localization? In this paper we propose two methods that address this question. The first approach evaluates the usefulness of tactile data from different sensors by means of a Particle Filter Localization algorithm. The second approach, using an Iterative Closed Point algorithm, evaluates the synergy of tactile sensors and the geometry of robotic hands.We prove, using both approaches as a novelty, that the sensor complexity does not affect the localization performance drastically. In particular, we demonstrate that it is possible to obtain similar performance with a simple fingertip sensor, designed by us, than with more complex tactile sensors. A comparison, based on simulated data for an ideal sensor and experimental data for another three sensors, corroborates our proposal, showing the potential of our fingertip force sensor for tactile exploration and in-hand localization.

What Can Ontologies Do for Robot Design

In this paper we address the problem of automatic design of the abstract structure of a robot. The design is driven by the desired capabilities that the robot should be able to perform. To this aim, an extension for the IEEE Standard Ontology for Robotics and Automation has been developed. We present an intelligent system which infers abstract robot morphologies from this ontology by relating robot actions to necessary structural parts. Then, these abstract structures can be materialized into physical robots that are able to perform requested capabilities. We show this implementation using a modular robotics platform as a demonstrator.

A Comparison of Tactile Sensors for In-Hand Object Location

This work presents an extensive analysis of the usefulness of tactile sensors for in-hand object localization. Our analysis is based on a previous work where we proposed a method for the evaluation of tactile data using two algorithms: a Particle Filter algorithm and an Iterative Closest Point algorithm. In particular, we present a comparison of six different sensors, including two pairs of sensors based on similar technology, showing how the design and distribution of tactile sensors can affect the performance. Also, together with previous results where we demonstrated the importance of the synergy between tactile data and hand geometry, we corroborate that it is possible to obtain more similar performance with a simple fingertip sensor, than with more complex and expensive tactile sensors.

Slip Detection in Robotic Hands with Flexible Parts

It is well known that tactile sensing is of major importance in robots that interact with the environment. It provides relevant information for the robot to detect contacts with surfaces and manipulate objects. Flexible fingers have demonstrated its usefulness in the field. Due to their high flexibility they can detect contacts and can be safely used to control forces with high accuracy over any object. Among their advantages are low weight, low kinetic energy, low inertia, high flexibility, durability and resistance. In this paper, we demostrate how to take advantage of flexible links in order to detect slipping. We show how the same principle can be applied in force sensors based on flexible parts. In particular, we also show the slip detection with a simple and low cost sensor based on flexible beam deformation, with the finger torque sensor of the Barrett Hand, and with a 6 axis force sensor mounted in the wrist of an industrial robot.