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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 b...
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The current state of electronic component miniaturization coupled with the increasing efficiency in hardware and software allow the development of smaller and compact robotic systems. The convenience of using these small, simple, yet capable robots has gathered the research community's attention towards practical applications of swarm robotics. Thi...
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... However, normally, they tend to be utilized in a probelike fashion such as for surgical instruments and struggle to be arrayed [6]. Cirillo et al. presented a photo-diode-based tactile sensor with a 25-element array using photodetectors and one deformable surface [15,33]. However, it requires two proportionally large PCBs to facilitate the readout of the sensing elements and only detects normal force changes [33]. ...
... Cirillo et al. presented a photo-diode-based tactile sensor with a 25-element array using photodetectors and one deformable surface [15,33]. However, it requires two proportionally large PCBs to facilitate the readout of the sensing elements and only detects normal force changes [33]. A successful friction-based force and displacement three-axis photodiode-based optical tactile sensor (PapillArray) uses a camera obscura and quadrant photodiode to measure the force and displacement of each of nine different sensing units in a 3 × 3 sensing array [16,34], which also requires two PCBs, making the design somewhat bulky and challenging to miniaturize and restricts the sensor's versatility. ...
... The uSkin sensor [21] showcases a smaller thickness (5.85 mm), but uses a magnetic sensing method; magnetic methods are prone to (ferro)magnetic interference, which may limit their utility in industrial applications. The LiVec finger's thickness is also comparable to non-camera-based optical tactile sensors, such as Cirillo et al.'s dense optoelectronic sensor array with 25 photodiodeswith a 21 × 21 mm 2 sensitive area and a 10 mm deformable layer height [33]. However, it requires two stacked proportionally large PCBs compared to the sensitive area covered by a case (90 mm × 21 mm), which is over four-times larger than the sensitive area. ...
Real-time multi-axis distributed tactile sensing is a critical capability if robots are to perform stable gripping and dexterous manipulation, as it provides crucial information about the sensor–object interface. In this paper, we present an optical-based six-axis tactile sensor designed in a fingertip shape for robotic dexterous manipulation. The distributed sensor can precisely estimate the local XYZ force and displacement at ten distinct locations and provide the global XYZ force and torque measurements. Its compact size, comparable to that of a human thumb, and minimal thickness allow seamless integration onto existing robotic fingers, eliminating the need for complex modifications to the gripper. The proposed sensor design uses a simple, low-cost fabrication method. Moreover, the optical transduction approach uses light angle and intensity sensing to infer force and displacement from deformations of the individual sensing units that form the overall sensor, providing distributed six-axis sensing. The local force precision at each sensing unit in the X, Y, and Z axes is 20.89 mN, 19.19 mN, and 43.22 mN, respectively, over a local force range of approximately ±1.5 N in X and Y and 0 to −2 N in Z. The local displacement precision in the X, Y, and Z axes is 56.70 μm, 50.18 μm, and 13.83 μm, respectively, over a local displacement range of ±2 mm in the XY directions and 0 to −1.5 mm in Z (i.e., compression). Additionally, the sensor can measure global torques, Tx, Ty, and Tz, with a precision of of 1.90 N-mm, 1.54 N-mm, and 1.26 N-mm, respectively. The fabricated design is showcased by integrating it with an OnRobot RG2 gripper and illustrating real-time measurements during in simple demonstration task, which generated changing global forces and torques.
... However, normally, they tend to be utilized in probe-like uses such as for surgical instruments and struggle to be arrayed [6]. Cirillo et al. presented a photo-diode-based tactile sensor with a 25-element array using photodetectors and one deformable surface [15,33]. However, it requires two proportionally large PCBs to facilitate the readout of the sensing elements and only detects normal force changes [33]. ...
... Cirillo et al. presented a photo-diode-based tactile sensor with a 25-element array using photodetectors and one deformable surface [15,33]. However, it requires two proportionally large PCBs to facilitate the readout of the sensing elements and only detects normal force changes [33]. A successful friction-based force and displacement 3-axis photodiode-based optical tactile sensor (PapillArray) uses a camera obscura and quadrant photodiode to measure the force and displacement of each of nine different sensing units in a 3 × 3 sensing array [16,34], which also requires two PCBs, making the design somewhat bulky, challenging to miniaturize and restricts the sensor versatility. ...
... The uSkin sensor [21] showcases a smaller thickness (5.85 mm), but uses a magnetic sensing method; magnetic methods are prone to (ferro)magnetic interference, which may limit their utility in industrial applications. The LiVec finger thickness is also comparable to non-camera-based optical tactile sensors, such as Cirillo et al. dense optoelectronic sensor array with 25 photodiode array with a 21 × 21 mm 2 sensitive area, and a 10 mm deformable layer height [33]. However it requires two stacked proportionally large PCBs compared to the sensitive area covered by a case (90 mm × 21 mm), which is over 4 times larger than the sensitive area. ...
Real-time multi-axis distributed tactile sensing is a critical capability if robots are to perform stable gripping and dexterous manipulation, as it provides crucial information about the sensor-object interface. In this paper, we present an optical-based 6-axis tactile sensor designed in a fingertip shape for robotic dexterous manipulation. The distributed sensor can precisely estimate local XYZ force and displacement at ten distinct locations, and provide global XYZ force and torque measurements. Its compact size, comparable to that of a human thumb, and minimal thickness allow seamless integration onto existing robotic fingers, eliminating the need for complex modifications to the gripper. The proposed sensor design uses a simple, low-cost fabrication method. Moreover, the optical transduction approach uses light angle and intensity sensing to infer force and displacement from deformations of individual sensing units that form the overall sensor, providing distributed 6-axis sensing. The local force precision at each sensing unit in the X, Y, and Z axes is 20.89 mN, 19.19 mN, and 43.22 mN, respectively, over an local force range of approximately ±1.5 N in X and Y and 0 to -2 N in Z. The local displacement precision in the X, Y and Z axes is 56.70 μm, 50.18 μm and 13.83 μm, respectively, over a local displacement range of ±2 mm in the XY directions and 0 to -1.5mm in Z (i.e., compression). Additionally, the sensor can measure global torques, Tx, Ty and Tz, with a precision of of 1.90 N-mm, 1.54 N-mm and 1.26 N-mm, respectively. The fabricated design is showcased by integrating it with an OnRobot RG2 gripper and illustrating real-time measurements during in simple demonstration task which generate changing global forces and torques.
... Hence, researchers are required to integrate and even develop their own tactile sensors. Sensor technologies in literature include piezoresistive [5], capacitive [6], thermoelectric [7], optoelectronic [8] and more. This heterogeneity in sensor hardware makes it difficult to compare the performance of control algorithms as the nature of the sensor is strongly intertwined with any control algorithm exploiting it. ...
... We argue that there is plenty of room for accessible, open-source tactile fingertips with readily interpretable data outputs. We present a set of narrow fingertips specifically suited for narrow object manipulation and demonstrate their potential in two actively explored problems in the state-of-the-art: cloth edge tracing [11] and cable tracing [8], [12]. ...
... The tactile fingertips are uniquely suited towards manipulation of narrow objects, while being thinner than e.g. GelSight sensors and the optoelectronic sensors in [8], allowing for a compliant design. Additionally, sensor platforms like ours are more accessible than GelSight sensors in terms of cost and both hardware and software integration, further incentivising benchmarking in tactile robotics. ...
The development of tactile sensing and its fusion with computer vision is expected to enhance robotic systems in handling complex tasks like deformable object manipulation. However, readily available industrial grippers typically lack tactile feedback, which has led researchers to develop and integrate their own tactile sensors. This has resulted in a wide range of sensor hardware, making it difficult to compare performance between different systems. We highlight the value of accessible open-source sensors and present a set of fingertips specifically designed for fine object manipulation, with readily interpretable data outputs. The fingertips are validated through two difficult tasks: cloth edge tracing and cable tracing. Videos of these demonstrations, as well as design files and readout code can be found at https://github.com/RemkoPr/icra-2023-workshop-tactile-fingertips.
... The sensor allows the estimation of the in-hand pose of the BH, which can be used to compensate picking errors by adjusting the robot trajectory during the insertion/placing phases. The main objective of this work is to demonstrate that the tactile sensor, developed by some of the authors [27], can be used to tackle complex tasks by using both machine learning and model-based methods on the same tactile data, selecting the most suitable one depending on the specific problem to solve. As model-based techniques we intend methods that do not require the acquisition of an extensive training set and a subsequent training phase to determine a possibly large number of hyperparameters, that, on the contrary, are required by machine-learning techniques. ...
... , 25 hereafter. The interested reader can find additional details about the hardware and the elaboration system software in [27]. Fig. 3 reports the taxel distribution with respect to the reference frame, by highlighting the corresponding voltage signal v i of each taxel. ...
Robust manipulation of mechanical parts in different grasping configurations is a challenging problem in autonomous robotic assembly that can be overcome by adopting suitable mechatronic solutions. This article proposes a tactile-sensor-based approach that exploits in-hand pose estimation and contact perception to compensate for unavoidable picking, placing, and insertion errors that may occur during task assembly execution under uncertain/perturbed conditions. The main objective of this work is to demonstrate how the use of tactile data, together with both machine learning and model-based methods, allows us to obtain an advanced system able to successfully complete a task that requires the manipulation of boltlike fasteners with different shapes and grasped in different poses. Experiments carried out using the proposed robotic system are reported for a specific assembly task in order to evaluate the effectiveness of the proposed solution. By means of suitable calibration procedures exploiting the same methods proposed here, the system can be easily adapted to different objects and shapes.
... The alternative to such artificial skins, is to use an array of discrete sensors, however, the new EIT-based technology offers the following advantages: minimal wiring; flexible; scalable; continuous sensing across the domain; easy to manufacture; low power consumption and low cost [3,12]. The e-skin has become a very important area of development in the past few years [13][14][15][16][17][18], whether it is for robots that are like humans, or robots that needs to work in a safe environment with humans or other robots. This paper covers an important area of soft robotics by providing methods of performance evaluation. ...
Electrical impedance tomography (EIT) is a promising technique for large area tactile sensing for robotic skin. This study presents a novel EIT-based force and touch sensor that features a latex membrane acting as soft skin and an ionic liquid domain. The sensor works based on fringing field EIT where the touch or force leads to a deformation in the latex membrane causing detectable changes in EIT data. This article analyses the performance of this electronic skin in terms of its dynamical behaviour, position accuracy and quantitative force sensing. Investigation into the sensor’s performance showed it to be hypersensitive, in that it can reliably detect forces as small as 64 mN. Furthermore, multi-touch discrimination and annular force sensing is displayed. The hysteresis in force sensing is investigated showing a very negligible hysteresis. This is a direct result of the latex membrane and the ionic liquid-based domain design compared to more traditional fabric-based touch sensors due to the reduction in electromechanical coupling. A novel test is devised that displayed the dynamic performance of the sensor by showing its ability to record a 1 Hz frequency, which was applied to the membrane in a tapping fashion. Overall, the results show a considerable progress in ionic liquid EIT-based sensors. These findings place the EIT-based sensors that comprise a liquid domain, at the forefront of research into tactile robotic skin.
... Considering the good performance and the limited dimensions of the new off-the-shelf ToF sensors, the authors of this paper presented in [14] a new pre-touch sensing solution, fully integrated in the pre-existent tactile sensors developed by some of the authors in the last ten years [17], [18]. The main objective is the manipulation of Deformable Linear Objects (DLOs), e.g., thin electrical wires, within the activities of H2020 REMODEL project 1 . ...
... The starting sensorized finger with integrated tactile sensor is the one detailed in [18]. It consists of a sensing pad with a matrix of 5 × 5 taxels based on optoelectronic technology. ...
... The signals are managed by an onboard Microchip PIC16F19176 microcontroller, and interfaced with the PC trough a standard serial bus. Details about tactile sensor characterization can be found in [18]. The proximity sensing system has been designed in order to be compatible with the existing tactile sensor solution. ...
... Tactile sensation is a highly desired function in the robotics industry [1][2][3][4][5][6][7][8][9]. Makihata [5] recently reported that the requirements for tactile sensors include large-area sensing capability, which requires a large number of sensors, rapid response time, and low cost. ...
... Although the integration of sensors with readout circuits is a crucial technology required for large-area, high-resolution tactile sensing, to date, few integrated tactile sensors have been identified, owing to strict thermal budgets and process compatibility. Tactile sensors are typically integrated with the readout circuit in system levels [1][2][3][4][5][6][7][8][9][10][11][12][13]. In this study, an integrated piezoresistive normal force sensor was presented. ...
Tactile sensation is a highly desired function in robotics. Furthermore, tactile sensor arrays are crucial sensing elements in pulse diagnosis instruments. This paper presents the fabrication of an integrated piezoresistive normal force sensor through surface micromachining. The force sensor is transferred to a readout circuit chip via a temporary stiction effect handling process. The readout circuit chip comprises two complementary metal-oxide semiconductor operational amplifiers, which are redistributed to form an instrumentation amplifier. The sensor is released and temporarily bonded to the substrate before the transfer process due to the stiction effect to avoid the damage and movement of the diaphragm during subsequent flip-chip bonding. The released sensor is pulled off from the substrate and transferred to the readout circuit chip after being bonded to the readout circuit chip. The size of the transferred normal force sensor is 180 μm × 180 μm × 1.2 μm. The maximum misalignment of the flip-chip bonding process is approximately 1.5 μm, and sensitivity is 93.5 μV/μN/V. The routing of the piezoresistive Wheatstone bridge can be modified to develop shear force sensors; consequently, this technique can be used to develop tactile sensors that can sense both normal and shear forces.
... Considering the good performance and the limited dimensions of the new off-theshelf ToF sensors, the authors believe that they represent the best enabling technology for pre-touch sensing. In particular, starting from the tactile sensors already developed by some of the authors in the last ten years [16,17], in this paper the authors present a new pre-touch sensing solution, fully integrated in the pre-existent tactile sensors, able to recognize the shape of the objects through a specific scanning procedure. The work focuses on Deformable Linear Objects (DLO) manipulation, which represents one of the main objectives of H2020 REMODEL project https://remodel-project.eu/ (accessed on 2 September 2021). ...
... Starting from the tactile sensor developed and presented by the authors in [16,17], the pre-touch (proximity) sensor prototype described in this paper has been designed in order to be compatible with the existing tactile sensor solution from both mechanics and hardware/software points of view. In particular, the compatibility of the new sensors with the mentioned tactile one represented the principal design constraint, e.g., the new board has been designed in such a way it can be installed on the rear side of the tactile sensor and respecting the electrical and software interface of the latter. ...
... With the configuration used in this specific application the proximity sensor is able to measure the distance from an object with millimetric accuracy in a range from 0.5 mm to 100 mm. If the reader is interested in having more details about the PC side-SW design and implementation, they can refer to [17]. ...
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.
... Section 2 briefly recalls main features of the tactile sensor used in this paper. The interested reader can find a detailed characterization of the technology in [22]. Section 2 proposes a new optimized algorithm to estimate the shape of the grasped wire, by improving the estimation quality with respect to the solution presented by the authors in [23]. ...
... The contact information is obtained from the deformation of this layer measured by the optical sensing points, here called "taxels". The main characteristics of the sensor, detailed in [22], are summarized in Table 1. ...
... The location of each taxel is defined as t ij by exploiting its row and column indices within the matrix. The interested reader can find all details of the electronic and mechanical design in [22]. ...
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.
Rapid deployment of automation in today's world has opened up exciting possibilities in the realm of design and fabrication of soft robotic grippers endowed with sensing capabilities. Herein, a novel design and rapid fabrication by 3D printing of a mechano‐optic force sensor with a large dynamic range, sensitivity, and linear response, enabled by metamaterials‐based structures, is presented. A simple approach for programming the metamaterial's behavior based on mathematical modeling of the sensor under dynamic loading is proposed. Machine learning models are utilized to predict the complete force–deformation profile, encompassing the linear range, the onset of nonlinear behavior, and the slope of profiles in both bending and compression‐dominated regions. The design supports seamless integration of the sensor into soft grippers, enabling 3D printing of the soft gripper with an embedded sensor in a single step, thus overcoming the tedious and complex and multiple fabrication steps commonly applied in conventional processes. The sensor boasts a fine resolution of 0.015 N, a measurement range up to 16 N, linearity (adj. R²–0.991), and delivers consistent performance beyond 100 000 cycles. The sensitivity and range of the embedded mechano‐optic force sensor can be easily programmed by both the metamaterial structure and the material's properties.
