This paper presents a multi-axis low-cost soft magnetic tactile sensor with a high force range for force feedback in robotic surgical systems. The proposed sensor is designed to fully decouple the output response for normal, shear and angular forces. The proposed sensor is fabricated using rapid prototyping techniques and utilizes Neodymium magnets embedded in an elastomer over Hall sensors such that their displacement produces a voltage change that can be used to calculate the applied force. The initial spacing between the magnets and the Hall sensors is optimized to achieve a large displacement range using finite element method (FEM) simulations. The experimental characterization of the proposed sensor is performed for applied force in normal, shear and 45° angular direction. The force sensitivity of the proposed sensor in normal, shear and angular directions is 16 mV/N, 30 mV/N and 81 mV/N, respectively, with minimum mechanical crosstalk. The force range for the normal, shear and angular direction is obtained as 0–20 N, 0–3.5 N and 0–1.5 N, respectively. The proposed sensor shows a perfectly linear behavior and a low hysteresis error of 8.3%, making it suitable for tactile sensing and biomedical applications. The effect of the material properties of the elastomer on force ranges and sensitivity values of the proposed sensor is also discussed.

The study proposed the classification and recognition of hand gestures using electromyography (EMG) signals for controlling the upper limb prosthesis. In this research, the EMG signals were measured through an embedded system by wearing a band of MYO gesture control. In order to observe the behavior of these change movements, the EMG data was acquired from 10 healthy subjects (five male and five females) performing four upper limb movements. After extracting EMG data from MYO, the supervised classification approach was applied to recognize the different hand movements. The classification was performed with a 5-fold cross-validation technique under the supervision of Quadratic discriminant analysis (QDA), support vector machine (SVM), random forest, gradient boosted, ensemble (bagged tree), and ensemble (subspace K-Nearest Neighbors) classifier. The execution of these classifiers shows the overall accuracy of 83.9% in the case of ensemble (bagged tree) which is higher than other classifiers. Additionally, in this research an embedded system-based classification approach of hand movement was used for designing an upper limb prosthesis. This approach is different than previous techniques as MYO is used with an external Bluetooth module and different libraries that make its movement and performance boundless. The results of this study also inferred the operations which were easy for hand recognition and can be used for developing a powerful, efficient, and flexible prosthetic design in the future.

The design and fabrication of a Polyvinylidene fluoride (PVDF) based, mouse (or rodent) whisker mimicking, tactile sensor is presented. Unlike previous designs reported in the literature, this sensor mimics the mouse whisker not only mechanically, but it also makes macro movements just like a real mouse whisker in a natural environment. We have developed a mathematical model and performed finite element analysis using COMSOL, in order to optimise the whisker to have the same natural frequency as that of a biological whisker. Similarly, we have developed a control system that enables the whisker mimicking sensor to vibrate at variable frequencies and conducted practical experiments to validate the response of the sensor. The natural frequency of the whisker can be designed anywhere between 35 and 110 Hz, the same as a biological whisker, by choosing different materials and physical dimensions. The control system of this sensor enables the whisker to vibrate between 5 and 236 Hz.

Navigating an autonomous vehicle through a circular ramp to join a multilane highway having high-density traffic is a very challenging task. Occupant and vehicle safety are the major considerations while establishing merging scenarios. This article proposes and experimentally implements safe and tactical navigational procedures for merging and leaving the highway scenario using the rendezvous guidance (RG) technique and its modified form. Test scenarios have been established for navigating AVs to merge and leave the highway on a multilane highway with or without the presence of any other vehicle in the zone. In addition, the navigation with enhanced performance of the modified RG algorithm is also established and compared to the conventional RG algorithm. The results indicate that time is reduced considerably by using the modified RG technique. The experimental and simulation results are compared, and their results are the same.

Purpose: This paper aims to introduce a sensorized surgical grasper with a novel flexible capacitive tactile force sensor integrated within the surgical grasper for minimally invasive surgery (MIS) and robot-assisted MIS (RMIS) procedures. Design/methodology/approach: The proposed sensor offers a unique configuration of sensing electrodes with one top excitation electrode and three bottom electrodes enabling the measurement of normal and shear forces without incorporating any complex decoupling algorithms. The design of the sensor is optimized using finite-element method simulations, ensuring efficiency and reliability. Findings: Experimental validation, real-time sensor response and application in lump detection through stiffness assessment demonstrate the decoupled force response (0–5 N normal range and 0–2 N shear range) with high sensitivity 0.0124/N, repeatability and hysteresis response with 5.65% and 4.7% errors respectively. Originality/value: The compact design of the sensor makes it compliant with surgical graspers and therefore enhances the overall efficiency of robotic surgical procedures. The sensorized surgical grasper is fabricated using conventional machining and rapid prototyping techniques, presenting a cost-effective solution for adoption.