This study presents the design and evaluation of a prototype snake-like robot that possesses an actuation system based on shape memory alloys (SMAs). The device is constructed based on a modular structure of links connected by two degrees of freedom links utilizing Cardan joints, where each degree of freedom is actuated by an agonist–antagonist mechanism using the SMA spring-shaped actuators to generate motion, which can be easily replaced once they reach a degradation point. The methodology for programming the spring shape into the SMA material is described in this work, as well as the instrumentation required for the monitoring and control of the actuators. A simplified design is presented to describe the way in which the motion is performed and the technical difficulties faced in manufacturing. Based on this information, the way in which the design is adapted to generate a feasible robotic system is described, and a mathematical model for the robot is developed to implement an independent joint controller. The feasibility of the implementation of the SMA actuators regarding the motion of the links is verified for the case of a joint, and the change in the shape of the snake robot is verified through the implementation of a set of tracking references based on a central pattern generator. The generated tracking results confirm the feasibility of the proposed mechanism in terms of performing snake gaits, as well as highlighting some of the drawbacks that should be considered in further studies.

This article presents the design and implementation of a linear actuator based on NiTi Shape Memory Alloys with temperature and position measurements based on a magnetic sensor array and a set of thermistors. The position instrumentation is contact free to avoid friction perturbations; the position signal conditioning is carried out through the calculation of the response of each magnetic sensor, selecting the closest sensor to ensure accurate results on the full range of movement. Experimental results validate the accuracy of the position sensing with a competitive behaviour.

In this work, the position control of a cable-driven soft robot is proposed through the approximation of its kinematic model. This approximation is derived from artificial learning rules via neural networks and experimentally observed data. To improve the learning process, a combination of active sampling and Model Agnostic Meta Learning is carried out to improve the data based model to be used in the control stage through the inverse velocity kinematics derived from the data based modeling along with a self differentiation procedure to come up with the pseudo inverse of the robot Jacobian. The proposal is verified in a designed and constructed cable-driven soft robot with three actuators and position measurement through a vision system with three-dimensional motion. Some preliminary assessments (tension and repeatability) were performed to validate the robot movement generation, and, finally, a 3D reference trajectory was tracked using the proposed approach, achieving competitive tracking errors.

Sensing antenna devices, that mimic insect antennae or mammal whiskers, is an active field of research that still needs new developments in order to become efficient and reliable components of robotic systems. This work reports a new result in the area of signal processing of these devices that allows to detect the instant of the impact of a flexible antenna with an object faster than other reported methods. Previous methods require the use of filters that introduce delays in the impact detection. A method based on the Super-Twisting algorithm is proposed here that avoids the use of these filters and reduces such delays improving the impact instant estimation. Experiments show that these delays can be reduced in more than 50%, allowing reliable estimation of the impact instant with an error of less than 5 ms in many cases requiring a limited computational effort.

Electric vehicles need continuous monitoring of the energy supply all the time to provide the user with accurate information about the available energy. However, an increase in the power consumed by the monitoring system may cause a significant decrease in the vehicles autonomy. This letter presents a monitoring and estimation system for an electric car with a hybrid energy supply based on supercapacitors and batteries based on an embedded system capable of monitoring the general current, the current from the battery system, the voltage in the battery system, the voltage in the supercapacitor system, estimating the value of the State of Charge from batteries and showing the measurements to the user with an OLED display. The proposed system performs similarly in the estimation but decreases the energy consumption by 99.9 % concerning laboratory systems.