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Disadvantages of conventional robotic systems include rigidity, multiple moving parts, and the need for elaborate safety mechanisms when used in human-machine interaction. Soft manipulators and grippers are gaining in popularity due to being able to handle large payloads whilst being lightweight, highly compliant, low-cost, and compactible or collapsible. Yet soft robots cannot make use of traditional rigid sensors to measure their pose or interaction with the environment. Perception in soft robotics needs to embrace alternative methods: sensors made from soft materials that perform robustly under compression and bending conditions; i.e, stretchable soft sensors that rely on (their) material and electrical properties to output signal measurements. However, many such sensors come with inherent drawbacks, including material incompatibility, fabrication complexity, and hysteresis. In this paper, we report on the use of multiple staggered optical waveguide sensors embedded in silicone. These stretchable optical waveguide sensors coated with a thin layer of gold were fabricated and integrated with a fabric-based, inflatable robot finger. An experimental study was performed to evaluate the sensor's responsiveness. We find that multi-curvature pose estimation (from 0.05-0.135 m-1) (from fully deflated to maximum inflation) can be acquired after integration with the inflatable robot finger. The sensor proves capable of measuring force information by way of interaction with the environment at multiple points along the gripper.

In recent years we have seen tremendous progress in the development of robotic solutions for minimally invasive surgery (MIS). Indeed, a number of robot-assisted MIS systems have been developed to product level and are now well-established clinical tools; Intuitive Surgical’s very successful da Vinci Surgical System a prime example. The majority of these surgical systems are based on the traditional rigid-component robot design that was instrumental in the third industrial revolution—especially within the manufacturing sector. However, the use of this approach for surgical procedures on or around soft tissue has come under increasing criticism. The dangers of operating with a robot made from rigid components both near and within a patient are considerable. The EU project STIFF-FLOP, arguably the first large-scale research programme on soft robots for MIS, signalled the start of a concerted effort among researchers to investigate this area more comprehensively. While soft robots have many advantages over their rigid-component counterparts, among them high compliance and increased dexterity, they also bring their own specific challenges when interacting with the environment, such as the need to integrate sensors (which also need to be soft) that can determine the robot’s position and orientation (pose). In this study, the challenges of sensor integration are explored, while keeping the surgeon’s perspective at the forefront of ourdiscussion. The paper critically explores a range of methods, predominantly those developed during the EU project STIFF-FLOP, that facilitate the embedding of soft sensors into articulate soft robot structures using flexible, optics-based lightguides. We examine different optics-based approaches to pose perception in a minimally invasive surgery settings, and methods of integration are also discussed.

Optical sensors have recently been proposed for sensing bending, linear strains and external forces in soft actuators. However, the susceptibility of these sensors to a number of stimuli makes it difficult to comprehend the resulting data output. We address this challenge through the introduction of a low-cost flexible bending sensor based upon the abrasion of optical channels. Such sensors are responsive to bending while being insensitive to internal pressure or external forces. The developed sensor is integrated into a soft pneumatic finger in order to obtain feedback of its curvature. We further demonstrate that the sensor is insensitive to normal forces applied on a blocked finger. Through this work, we propose a simple, low-cost sensor development technique towards addressing the challenge of decoupling forces and deformations in soft robots.

Notable advancements in shape sensing for flexible continuum robot arms can be observed. With a keen interest to develop surgical and diagnostic tools that can advance further and further into inaccessible spaces along tortuous pathways, such as the human body, a need for the precise determination of the robot’s pose arises. Whilst there have been techniques developed that use external sensors to observe the advancing robot from the outside to determine its location and orientation in space, there is an observable trend towards using integrated, internal sensors to measure these positional parameters. Especially in the medical world with its tough requirements on robot size, e.g., catheter-type robots, most pose-sensing approaches to date make use of a technique called Fiber Bragg Grating (FBG). FBG sensors make use of fibers that are grated, and the amount of bending can be determined with an appropriate optical interrogator. Although these fiber sensors have been successfully employed to measure the deformation and through advanced signal processing the pose of continuum catheters, they have a major drawback which is their exorbitant cost. To address this issue a different design and fabrication process is proposed to produce an affordable shape sensor that is highly flexible and can detect bending. The method of operation involves a segmented flexible robot arm with three waveguides in a 120-degrees configuration. The segments are made of silicone elastomer with channels that encapsulate light propagating internally, with a photodiode and light-emitting diode (LED) embedded in each individual channel. The prototype was developed and characterized for strain, and bending response detection.