Fingertip force control with embedded fiber Bragg grating sensors

Abstract—We describe the dynamic testing and control results obtained with an exoskeletal robot finger with embedded fiber optical sensors. The finger is inspired by the designs of arthropod limbs, with integral strain sensilla concentrated near the joints. The use of fiber Bragg gratings (FBGs) allows for embedded sensors with high strain sensitivity and immunity to electromagnetic interference. The embedded sensors are useful for contact detection and for control of forces during fine manipulation. The application to force control requires precise and high-bandwidth measurement of contact forces. We present a nonlinear force control approach that combines signals from an optical interrogator and conventional joint angle sensors to achieve accurate tracking of desired contact forces. I

Process for manufacturing shell membrane force and deflection sensor

A sensor for force is formed from an elastomeric cylinder having a region with apertures. The apertures have passageways formed between them, and an optical fiber is introduced into these passageways, where the optical fiber has a grating for measurement of tension positioned in the passageways between apertures. Optionally, a temperature measurement sensor is placed in or around the elastomer for temperature correction, and if required, a copper film may be deposited in the elastomer for reduced sensitivity to spot temperature variations in the elastomer near the sensors

Force and deflection sensor with shell membrane and optical gratings and method of manufacture

A sensor for force is formed from an elastomeric cylinder having a region with apertures. The apertures have passageways formed between them, and an optical fiber is introduced into these passageways, where the optical fiber has a grating for measurement of tension positioned in the passageways between apertures. Optionally, a temperature measurement sensor is placed in or around the elastomer for temperature correction, and if required, a copper film may be deposited in the elastomer for reduced sensitivity to spot temperature variations in the elastomer near the sensors

Tactile sensing and control of robotic manipulator integrating fiber Bragg grating strain-sensor

Tactile sensing is an instrumental modality of robotic manipulation, as it provides information that is not accessible via remote sensors such as cameras or lidars. Touch is particularly crucial in unstructured environments, where the robot’s internal representation of manipulated objects is uncertain. In this study we present the sensorization of an existing artificial hand, with the aim to achieve fine control of robotic limbs and perception of object’s physical properties. Tactile feedback is conveyed by means of a soft sensor integrated at the fingertip of a robotic hand. The sensor consists of an optical fiber, housing Fiber Bragg Gratings (FBGs) transducers, embedded into a soft polymeric material integrated on a rigid hand. Through several tasks involving grasps of different objects in various conditions, the ability of the system to acquire information is assessed. Results show that a classifier based on the sensor outputs of the robotic hand is capable of accurately detecting both size and rigidity of the operated objects (99.36 and 100% accuracy, respectively). Furthermore, the outputs provide evidence of the ability to grab fragile objects without breakage or slippage e and to perform dynamic manipulative tasks, that involve the adaptation of fingers position based on the grasped objects’ condition

Functional mimicry of Ruffini receptors with fibre Bragg gratings and deep neural networks enables a bio-inspired large-area tactile-sensitive skin

Collaborative robots are expected to physically interact with humans in daily living and the workplace, including industrial and healthcare settings. A key related enabling technology is tactile sensing, which currently requires addressing the outstanding scientific challenge to simultaneously detect contact location and intensity by means of soft conformable artificial skins adapting over large areas to the complex curved geometries of robot embodiments. In this work, the development of a large-area sensitive soft skin with a curved geometry is presented, allowing for robot total-body coverage through modular patches. The biomimetic skin consists of a soft polymeric matrix, resembling a human forearm, embedded with photonic fibre Bragg grating transducers, which partially mimics Ruffini mechanoreceptor functionality with diffuse, overlapping receptive fields. A convolutional neural network deep learning algorithm and a multigrid neuron integration process were implemented to decode the fibre Bragg grating sensor outputs for inference of contact force magnitude and localization through the skin surface. Results of 35 mN (interquartile range 56 mN) and 3.2 mm (interquartile range 2.3 mm) median errors were achieved for force and localization predictions, respectively. Demonstrations with an anthropomorphic arm pave the way towards artificial intelligence based integrated skins enabling safe human–robot cooperation via machine intelligence