Although conventional GelSight-based tactile and force/torque sensors excel in detecting objects' geometry and texture information while simultaneously sensing multi-axis forces, their performance is limited by the camera's lower frame rates and the inherent properties of the elastomer. These limitations restrict their ability to measure higher force ranges at high sampling frequencies. Besides, due to the coupling of the Gelsight sensor unit and multi-axis force/torque unit structurally, the force/torque measurement ranges of the Gelsight-based force/torque sensors are not adjustable. To address these weaknesses, this paper proposes the GEL-OPTOFORT sensor that combines a GelSight sensor and an optoelectronic sensor-based force/torque sensor.

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, Fibre Bragg grating (FBG) technology, inertial measurement unit (IMU) sensor 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{\deg}.

Along with their itchy bites, they spread serious diseases, like malaria, dengue or zika, which, as Microsoft co-founder Bill Gates has pointed out, kill more people every day than sharks have managed to do in an entire century. A Yale report released last year also suggests that climate change is going to make the problem worse. So, having early detection systems to promptly deploy preventive controls is crucial to protecting people. The Institute of Agrifood Research and Technology (IRTA) in Catalonia, Spain, has started to use artificial intelligence (AI), sensors, and satellite communications to automate the process of trapping mosquitoes and classifying them according to species, sex, age, and their potential for causing infection. Traps are not a new control technique.