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Self-healing polymers can address the damage susceptibility in soft robotics. However, in most cases, their healing requires a heat stimulus, provided by an external device. This paper presents a self-healing soft actuator with an integrated healable flexible heater, functioning as the stimuli-providing system. The actuator is constructed out of thermoreversible elastomers that are crosslinked by the Diels-Alder (DA) reaction, which provides the healing ability. The heater is manufactured from a DA-based composite network filled with 20 wt% carbon black to provide electrically conductive properties for resistive Joule heating. The flexibility of the heater does not compromise the actuator performance upon integration and the self-healing properties of both heater and actuator allow for damage repair. This includes very large damages, as both heater and actuator can recover (near 100%) from being cut completely in two pieces, using Joule heating at 90 °C with a bias voltage of about 30 V. The embedded heater, avoids the need for external intervention in the healing process, and provides healing quality assessment and a healing on-demand mechanism, paving the way for an optimum healing solution of damage resilient soft robots that require heat as a healing stimulus.

Self-healing materials can prolong the lifetime of structures and products by enabling the repairing of damage. However, detecting the damage and the progress of the healing process remains an important issue. In this study, self-healing, piezoresistive strain sensor fibers (ShSFs) are used for detecting strain deformation and damage in a self-healing elastomeric matrix. The ShSFs were embedded in the self-healing matrix for the development of self-healing sensor fiber composites (ShSFC) with elongation at break values of up to 100%. A quadruple hydrogen-bonded supramolecular elastomer was used as a matrix material. The ShSFCs exhibited a reproducible and monotonic response. The ShSFCs were investigated for use as sensorized electronic skin on 3D-printed soft robotic modules, such as bending actuators. Depending on the bending actuator module, the electronic skin was loaded under either compression (pneumatic-based module) or tension (tendon-based module). In both configurations, the ShSFs could be successfully used as deformation sensors, and in addition, detect the presence of damage based on the sensor signal drift. The sensor under tension showed better recovery of the signal after healing, and smaller signal relaxation. Even with the complete severing of the fiber, the piezoresistive properties returned after the healing, but in that case, thermal heat treatment was required. With their resilient response and self-healing properties, the supramolecular fiber composites can be used for the next generation of soft robotic modules.

On the heels of the successful launch of the inaugural edition of Focused Section on TMECH/AIM Emerging Topics, which was published in the August issue of TMECH in 2020, the second edition has experienced a difficult start due to worldwide pandemic outbreak. However, for this edition, a total of 86 submissions were received by January 8, 2021, on a broad range of mechatronics topics as mentioned before. Two rounds of rigorous review processes were then completed by this dedicated Editorial Board with the support of more than 210 anonymous peer reviewers, strictly following the high-quality standard and the scope of TMECH. A total of 29 articles were finally accepted for publication in this Focused Section and for presentation in AIM 2021 simultaneously. The submissions are from almost all continents in the world and representing various areas such as robotics, intelligent control, automotive systems, sensors and actuators, manufacturing, etc. Interesting and innovative technologic breakthroughs are observed in these submissions covering hardware structure, modeling, mechanisms, and algorithms in novel sensors and actuators, medical robotics and rehabilitation devices, soft robotics, bio-inspired robotic designs, service robots, data-driven and learning methods in robotics and control, motion planning and control, and control of autonomous vehicles and automotive systems.

The role of robotics is rapidly growing in importance in the particular non-industrial application domains, affecting society, economy and the environment. Robot systems are typically developed to address a specific technical, service-type or economical need, but often their broader impact is insufficiently investigated, if at all. For robots to play a beneficial role at society-level in the future, it is important to identify the mainstream directions in the field that enable the UN Sustainable Development Goals (SDGs), and encourage their development. Similarly, it is required to understand the negative impacts some applications can have on the achievement of the SDGs, and to ensure societies have the ability to prevent or mitigate them. Inspired by an exploration of the role of artificial intelligence in achieving the SDGs, this paper presents a preliminary version of a consensus-based expert elicitation process on the role of robots - as enabler or inhibitor - for a more sustainable future. For every SDG,the authors were able to identify potential positive and negative impacts of robotics. It remains difficult, though, to sketch a simple and comprehensive overview of the different ways in which robotic applications can unfold (direct or indirect) impact. Existing projects and studies are not intuitively comparable because they take many different directions and are not at the same level of abstraction, technological readiness, or implementation. Derived from the findings, recommendations on future policy developments are considered.

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The detection of human emotional states has received increasing attention over the last decades for a variety of applications and systems. However, detecting the intensity of the expressed emotion has not been investigated as much as detecting the type of the expressed emotion. To fill this gap, we investigate the utility of different facial and speech features for the detection of the intensity of the expressed emotion. To this end, we designed different Deep Neural Network architectures and applied them to RAVDESS dataset. Obtained results show speech signal features are better indicators of emotion intensity than facial features. However, in the absence of speech signal, finding emotion intensity by facial expressions, is more accurate for males in comparison to females. The difference between the accuracy of emotion intensity detection for two genders, motivated us to use speech signal for gender detection. The obtained results confirm the proposed model is better than state-of-the-art in emotion intensity detection and more robust in gender detection.

Research towards (compliant) actuators, especially redundant ones like the Series Parallel Elastic Actuator (SPEA), has led to the development of drive trains, which have demonstrated to increase efficiency, torque-to-mass-ratio, power-to-mass ratio, etc. In the field of robotics such drive trains can be implemented, enabling technological improvements like safe, adaptable and energy-efficient robots. The choice of the used motor and transmission system, as well as the compliant elements composing the drive train, are highly dependent of the application and more specifically on the allowable weight and size. In order to optimally design an actuator adapted to the desired characteristics and the available space, scaling laws governing the specific actuator can simplify and enhance the reliability of the design process. Although scaling laws of electric motors and links are known, none have been investigated for a complete redundant drive train. The present study proposes to fill this gap by providing scaling laws for electric motors in combination with their transmission system. These laws are extended towards parallelization, i.e. replacing one big motor with gearbox by several smaller ones in parallel. The results of this study show that the torque/mass ratio for a motor-gearbox can not be increased by parallelization, but that it can increase the torque/volume ratio. This is however only the case if a good topology is chosen.