Tactile sensors for robotic applications

In recent years, tactile sensing has become a key enabling technology to implement complex tasks by using robotic systems [...]

Optical Force/Tactile Sensors for Robotic Applications

Nowadays, robotic systems use tactile sensing as a key enabling technology to implement complex tasks. For example, manipulation and grasping problems strongly depend on the physical and geometrical characteristics of the objects; in fact, objects may be deformable or change their shape when in contact with the robot or the environment. For this reason, often, robots end effectors are equipped with sensorized fingers which can estimate the objects' features, forces, and contact locations. This is useful in a safe and efficient physical Human-Robot Interaction (pHRI) to perform cooperation and co-manipulation tasks while limiting damage from accidental impacts

Validating DLO models from shape observation

In this paper, the problem of fitting the model of deformable linear objects from the observation of the shape under the effect of known external forces like gravity is taken into account. The model of the deformable linear object is based on dynamic splines, allowing to obtain a reliable prediction of the object behavior while preserving a suitable efficiency and simplicity of the model. The object shape is measured by means of a calibrated vision system, and a fitting between the observed shape and the theoretical model is defined for validation. Experiments are executed in different conditions, showing the reliability of the proposed spline-based model

Wire Grasping by Using Proximity and Tactile Sensors

Nowadays robots have to be able to perform increasingly complex tasks. In grasping and manipulation, the knowledge of the environment and the pose of the target object are crucial for the correct execution of the task. Vision systems are widely used for environment and object perception, but they need to be finely calibrated to obtain high accuracy and they are not able to sense small objects like thin wires. Tactile sensors could be used to explore areas close to the target object, but this 'blind' physical interaction is not always feasible. This paper proposes a strategy to use a proximity sensor mounted on the robot's end effector to obtain a pose estimation of the target object that, in this study, is represented by a thin electrical wire

Proximity sensor for thin wire recognition and manipulation

In robotic grasping and manipulation, the knowledge of a precise object pose represents a key issue. The point acquires even more importance when the objects and, then, the grasping areas become smaller. This is the case of Deformable Linear Object manipulation application where the robot shall autonomously work with thin wires which pose and shape estimation could become difficult given the limited object size and possible occlusion conditions. In such applications, a vision-based system could not be enough to obtain accurate pose and shape estimation. In this work the authors propose a Time-of-Flight pre-touch sensor, integrated with a previously designed tactile sensor, for an accurate estimation of thin wire pose and shape. The paper presents the design and the characterization of the proposed sensor. Moreover, a specific object scanning and shape detection algorithm is presented. Experimental results support the proposed methodology, showing good performance. Hardware design and software applications are freely accessible to the reader

Vision-Based Robotic Solution for Wire Insertion with an Assigned Label Orientation

This paper tackles the problem of wire insertion in switchgear assembly according to the current regulations. In particular, the wire connections require that the wire label has to be oriented facing up in order to simplify and speed up testing and maintenance of the switchgear. The proposed approach exploits the a priori knowledge of the scenario with a calibrated RGB camera and a robotic arm to estimate both wire end pose and label position. The procedure combines several techniques (gradient base, trained classifier and stereo vision) to elaborate standard images in order to extract some wire features related to its shape and label. Specific frames are fixed according to estimated features and then used to correctly complete the task by using a robotic system. Experiments are reported to verify the effectiveness of the proposed approach

Tactile sensor data interpretation for estimation of wire features

At present, the tactile perception is essential for robotic applications when performing complex manipulation tasks, e.g., grasping objects of different shapes and sizes, distinguishing between different textures, and avoiding slips by grasping an object with a minimal force. Considering Deformable Linear Object manipulation applications, this paper presents an efficient and straightforward method to allow robots to autonomously work with thin objects, e.g., wires, and to recognize their features, i.e., diameter, by relying on tactile sensors developed by the authors. The method, based on machine learning algorithms, is described in-depth in the paper to make it easily reproducible by the readers. Experimental tests show the effectiveness of the approach that is able to properly recognize the considered object’s features with a recognition rate up to 99.9%. Moreover, a pick and place task, which uses the method to classify and organize a set of wires by diameter, is presented

Tactile sensors for parallel grippers: Design and characterization

Tactile data perception is of paramount importance in today’s robotics applications. This paper describes the latest design of the tactile sensor developed in our laboratory. Both the hardware and firmware concepts are reported in detail in order to allow the research community the sensor reproduction, also according to their needs. The sensor is based on optoelectronic technology and the pad shape can be adapted to various robotics applications. A flat surface, as the one proposed in this paper, can be well exploited if the object sizes are smaller than the pad and/or the shape recognition is needed, while a domed pad can be used to manipulate bigger objects. Compared to the previous version, the novel tactile sensor has a larger sensing area and a more robust electronic, mechanical and software design that yields less noise and higher flexibility. The proposed design exploits standard PCB manufacturing processes and advanced but now commercial 3D printing processes for the realization of all components. A GitHub repository has been prepared with all files needed to allow the reproduction of the sensor for the interested reader. The whole sensor has been tested with a maximum load equal to 15 N, by showing a sensitivity equal to 0.018 V/N. Moreover, a complete and detailed characterization for the single taxel and the whole pad is reported to show the potentialities of the sensor also in terms of response time, repeatability, hysteresis and signal to noise ratio

The PRISMA Hand II: A Sensorized Robust Hand for Adaptive Grasp and In-Hand Manipulation

Although substantial progresses have been made in building anthropomorphic robotic hands, lack of mechanical robustness, dexterity and force sensation still restrains wide adoption of robotic prostheses. This paper presents the design and preliminary evaluation of the PRISMA hand II, which is a mechanically robust anthropomorphic hand developed at the PRISMA Lab of University of Naples Federico II. The hand is highly underactuated, as the 19 finger joints are driven by three motors via elastic tendons. Nevertheless, the hand can performs not only adaptive grasps but also in-hand manipulation. The hand uses rolling contact joints, which is compliant in multiple directions. Force sensor are integrated to each fingertip in order to provide force feedback during grasping and manipulation. Preliminary experiments have been performed to evaluate the hand. Results show that the hand can perform various grasps and in-hand manipulation, while the structure can withstand severe disarticulation. This suggests that the proposed design can be a viable solution for robust and dexterous prosthetic hands