Proprioception and Control of a Soft Pneumatic Actuator Made of a Self-Healable Hydrogel.

The current evolutionary trends in soft robotics try to exploit the capacities of smart materials to achieve compact robotics designs with embodied intelligence. In this way, the number of elements that compose the soft robot can be reduced, as the smart material can cover different aspects (e.g., structure and sensorization) all in one. This work follows this tendency and presents a custom-designed hydrogel that exhibits two smart features, self-healing and ionic conductivity, used to build a pneumatic actuator. The self-healing capability provides the actuator's structure with the ability to self-repair from damages (e.g., punctures or cuts), an important quality to prolong the life cycle of the actuator. The ionic conductivity enables the actuator's proprioception: the structure itself serves as a curvature sensor. The behavior of this proprioceptive curvature sensor is analyzed in this work, studying its linearity, stability, and performance after a self-healing process. This sensor is also proposed as feedback in a closed-loop scheme to automatically control the actuator's curvature. A proportional-integral-derivative controller is designed based on an empirical model of the actuator's dynamics, and then validated in experimental tests, proving the proprioceptive sensor as proper feedback. These control tests are performed over undamaged and self-healed actuators, thus demonstrating all the capabilities of our soft material.

Passing through Open/Closed Doors: A Solution for 3D Scanning Robots.

In this article, a traversing door methodology for building scanning mobile platforms is proposed. The problem of passing through open/closed doors entails several actions that can be implemented by processing 3D information provided by dense 3D laser scanners. Our robotized platform, denominated as MoPAD (Mobile Platform for Autonomous Digitization), has been designed to collect dense 3D data and generate basic architectural models of the interiors of buildings. Moreover, the system identifies the doors of the room, recognises their respective states (open, closed or semi-closed) and completes the aforementioned 3D model, which is later integrated into the robot global planning system. This document is mainly focused on describing how the robot navigates towards the exit door and passes to a contiguous room. The steps of approaching, door-handle recognition/positioning and handle-robot arm interaction (in the case of a closed door) are shown in detail. This approach has been tested using our MoPAD platform on the floors of buildings composed of several rooms in the case of open doors. For closed doors, the solution has been formulated, modeled and successfully tested in the Gazebo robot simulation tool by using a 4DOF robot arm on board MoPAD. The excellent results yielded in both cases lead us to believe that our solution could be implemented/adapted to other platforms and robot arms.

Towards the automatic scanning of indoors with robots.

This paper is framed in both 3D digitization and 3D data intelligent processing research fields. Our objective is focused on developing a set of techniques for the automatic creation of simple three-dimensional indoor models with mobile robots. The document presents the principal steps of the process, the experimental setup and the results achieved. We distinguish between the stages concerning intelligent data acquisition and 3D data processing. This paper is focused on the first stage. We show how the mobile robot, which carries a 3D scanner, is able to, on the one hand, make decisions about the next best scanner position and, on the other hand, navigate autonomously in the scene with the help of the data collected from earlier scans. After this stage, millions of 3D data are converted into a simplified 3D indoor model. The robot imposes a stopping criterion when the whole point cloud covers the essential parts of the scene. This system has been tested under real conditions indoors with promising results. The future is addressed to extend the method in much more complex and larger scenarios.

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.