Shape sensing in continuum robotics enables stable actuation and control, as estimation of complex curvatures is essential for manoeuvring through complex environments, for applications in the manufacturing, aerospace, and medical industries, as well as space and rescue operations. This paper demonstrates the performance of an optoelectronic based shape sensing system integrated into a two-segment tendon actuated robotic manipulator. The sensing principle is proximity-intensity based sensing and utilises a convex shaped reflector for modulation of proximity during rotation in two degrees of freedom. For improved sensing performance, the shape sensing system utilises a simplified circuit design with features such as power switching properties for elimination of signal interference effects and for significant reduction in consumption of power, as well as inclusion of low friction tubes along the tendon routing paths, for reduced friction during large bending motions. A new streamlined technique for the calibration of the sensors is demonstrated, and a validation of the shape sensing performance shows improved estimates of tip position and orientation as well as shape of the robotic structure.

Three‐dimensional shape sensing in soft and continuum robotics is a crucial aspect for stable actuation and control in fields such as Minimally Invasive surgery, as the estimation of complex curvatures while using continuum robotic tools is required to manipulate through fragile paths. This challenge has been addressed using a range of different sensing techniques, for example, FBG technology, IMU networks or stretch sensors. Previously, an optics‐based method, using optoelectronic sensors was explored, offering a simple and cost‐effective solution for shape sensing in a flexible tendon‐actuated manipulator in two orientations. This was based on proximity‐modulated angle estimation and has been the basis for the shape‐sensing method addressed in this paper. The improved and miniaturized technique demonstrated in this paper is based on the use of a spherically shaped reflector with optoelectronic sensors integrated into a tendon actuated robotic manipulator. Upgraded sensing capability is achieved using optimization of the spherical reflector shape in terms of sensor range and resolution, and improved calibration is achieved through the integration of spherical bearings for friction‐free motion. Shape estimation is achieved in two orientations upon calibration of sensors, with a maximum Root Mean Square Error (RMS) of 3.37°.  

This paper presents the development and implementation of a low-cost, portable scale utilizing a smartphone and image  processing technology. The main objective of this research is to explore the potential of using a compliant mechanism, markers, and  image processing techniques to accurately determine the weight of an object. We designed a 3D printed platform fitted with a  webcam to capture images of white markers on a black surface. The Image Processing Toolbox on MATLAB was used to detect  two parameters, the number of white pixels and the centroid positions of the white pixels with respect to the centre of the image in  each marker. Calibration is carried out to convert these two parameters into weight, hence accurately estimating the weight of an  object placed on the platform.