This review investigates the latest advancements in Multi-Robot Systems (MRSs) and soft robotics, with a particular focus on their integration and emerging opportunities. An MRS extends principles from distributed artificial intelligence and coordination frameworks, enabling efficient collaboration in robotic applications such as object manipulation, navigation, and transportation. Soft robotics employs flexible materials and biomimetic designs to improve adaptability in unstructured environments, with applications in manufacturing, sensing, actuation, and modeling. Unlike previous reviews, which often address these fields independently, this work emphasizes their integration, identifying key challenges such as nonlinear dynamics, hyper-redundant configurations, and adaptive control. This review discusses recent advancements in locomotion, coordination, and simulation, offering insights into the development of adaptive and collaborative robotic systems across diverse applications.

This paper presents a new soft robotic hand exoskeleton for rehabilitation and movement assistance. The proposed device is based on a novel design of a PneuNet‐type pneumatic actuator; this novel actuator design allows larger bending motions while requiring less operating pressure; additionally, the actuator has an embedded sensor that allows an accurate trajectory tracking and control. The proposed design allows safe and controlled flexion movements for each one of the fingers, which is essential for effective rehabilitation and assistance tasks. The exoskeleton effectiveness was assessed by a physical therapist, and a modified version of the Sollerman test was used. Results obtained from the evaluation procedures provided insights into the exoskeleton performance and its efficacy. Preliminary conclusions are drawn based on the findings, and potential areas for further improvement are discussed. This research contributes to the development of an advanced soft robotic hand exoskeleton for rehabilitation and movement assistance, offering controlled flexion movements and improved functionality. This study demonstrates the potential of soft actuator technology in rehabilitation, presenting new possibilities for hand trauma recovery.

Human–robot collaborative systems have been adopted by manufacturing organizations with the objective of releasing physical workload to the human factor. However, the roles and responsibilities of human operators in these semi-automated systems have not been properly analyzed. This might carry important consequences in the cognitive dimension of ergonomics, which then contradicts the main well-being goals of collaborative work. Therefore, we designed a series of collaborative scenarios where we shifted the assignment of work responsibilities between humans and robots while executing a quality inspection task. Variations in the state of cognitive ergonomics were estimated with subjective and objective techniques via workload tests and physiological responses respectively. Furthermore, we introduced a work design framework based on 50 state-of-the-art applications for a structured implementation of human–robot collaborative systems that contemplates the underlying organizational and technological components necessary to fulfill its basic functionalities. Human operators that possessed responsibility roles over collaborative robots presented better results in terms of cognitive workload and spare mental capacity alike. In this regard, mental demand is seen as a key workload variable to consider when designing collaborative work in current manufacturing settings.

In the last decade, quadrotors have gained popularity among industry and academia due to their capabilities and the various applications in which they can be found. In addition to the above, because this is an underactuated system, researchers have found it a great challenge to control. Despite this, there is a wide variety of methodologies in the literature to control this type of system. Based on the above, this work proposed an alternative to trajectory tracking control for quadrotor unmanned aerial vehicles (UAV). The problem was divided into two main control loops: an outer control loop for the position coordinates, tackled through linear active disturbance rejection controllers (ADRC), and an inner control loop related to the orientation variables, addressed via robust proportional-integral-differential (PID) controllers. Furthermore, a generalized proportional integral observer (GPIO) was implemented to estimate the velocity and internal and external disturbances; therefore, the control strategy only depended on the attitude (position and orientation) quadrotor measurements. Then, the control performance was tested through numerical simulations and experimental tests, including wind disturbance inputs.