Mitochondria are cellular organelles involved in generating energy to power various processes in the cell. Although the pivotal role of mitochondria in neurogenesis was demonstrated (first in animal models), very little is known about their role in human embryonic neurodevelopment and its pathology. In this respect human-induced pluripotent stem cells (hiPSC)-derived cerebral organoids provide a tractable, alternative model system of the early neural development and disease that is responsive to pharmacological and genetic manipulations, not possible to apply in humans. Although the involvement of mitochondria in the pathogenesis and progression of neurodegenerative diseases and brain dysfunction has been demonstrated, the precise role they play in cell life and death remains unknown, compromising the development of new mitochondria-targeted approaches to treat human diseases. The cerebral organoid model of neurogenesis and disease in vitro provides an unprecedented opportunity to answer some of the most fundamental questions about mitochondrial function in early human neurodevelopment and neural pathology. Largely an unexplored territory due to the lack of tools and approaches, this review focuses on recent technological advancements in fluorescent and molecular tools, imaging systems, and computational approaches for quantitative and qualitative analyses of mitochondrial structure and function in three-dimensional cellular assemblies-cerebral organoids. Future developments in this direction will further facilitate our understanding of the important role or mitochondrial dynamics and energy requirements during early embryonic development. This in turn will provide a further understanding of how dysfunctional mitochondria contribute to disease processes.
Living beings modulate the impedance of their joints to interact proficiently, robustly, and safely with the environment. These observations inspired the design of soft articulated robots with the development of Variable Impedance and Variable Stiffness Actuators. However, designing them remains a challenging task due to their mechanical complexity, encumbrance, and weight, but also due to the different specifications that the wide range of applications requires. For instance, as prostheses or parts of humanoid systems, there is currently a need for multi-degree-of-freedom joints that have abilities similar to those of human articulations. Toward this goal, we propose a new compact and configurable design for a two-degree-of-freedom variable stiffness joint that can match the passive behavior of a human wrist and ankle. Using only three motors, this joint can control its equilibrium orientation around two perpendicular axes and its overall stiffness as a one-dimensional parameter, like the co-contraction of human muscles. The kinematic architecture builds upon a state-of-the-art rigid parallel mechanism with the addition of nonlinear elastic elements to allow the control of the stiffness. The mechanical parameters of the proposed system can be optimized to match desired passive compliant behaviors and to fit various applications (e.g., prosthetic wrists or ankles, artificial wrists, etc.). After describing the joint structure, we detail the kinetostatic analysis to derive the compliant behavior as a function of the design parameters and to prove the variable stiffness ability of the system. Besides, we provide sets of design parameters to match the passive compliance of either a human wrist or ankle. Moreover, to show the versatility of the proposed joint architecture and as guidelines for the future designer, we describe the influence of the main design parameters on the system stiffness characteristic and show the potential of the design for more complex applications
Robotic hand engineers usually focus on finger capabilities, often disregarding the palm contribution. Inspired by human anatomy, this paper explores the advantages of including a flexible concave palm into the design of a robotic hand actuated by soft synergies. We analyse how the inclusion of an articulated palm improves finger workspace and manipulability. We propose a mechanical design of a modular palm with two elastic rolling-contact palmar joints, that can be integrated on the Pisa/IIT SoftHand, without introducing additional motors. With this prototype, we evaluate experimentally the grasping capabilities of a robotic palm. We compare its performance to that of the same robotic hand with the palm fixed, and to that of a human hand. To assess the effective grasp quality achieved by the three systems, we measure the contact area using paint-transfer patterns in different grasping actions. Preliminary grasping experiments show a closer resemblance of the soft-palm robotic hand to the human hand. Results evidence a higher adaptive capability and a larger involvement of all fingers in grasping.
To physically interact with a rich variety of environments and to match situation-dependent requirements, humans adapt both the force and stiffness of their limbs. Reflecting this behavior in prostheses may promote a more natural and intuitive control and, consequently, improve prostheses acceptance in everyday life. This pilot study proposes a method to control a prosthetic robot hand and its impedance, and explores the utility of variable stiffness when performing activities of daily living and physical social interactions. The proposed method is capable of a simultaneous and proportional decoding of position and stiffness intentions from two surface electro-myographic sensors placed over a pair of antagonistic muscles. The feasibility of our approach is validated and compared to existing control modalities in a preliminary study involving one prosthesis user. The algorithm is implemented in a soft under-actuated prosthetic hand (SoftHand Pro). Then, we evaluate the usability of the proposed approach while executing a variety of tasks. Among these tasks, the user interacts with other 12 able-bodied subjects, whose experiences were also assessed. Several statistically significant aspects from the System Usability Scale indicate user's preference of variable stiffness control over low or high constant stiffness due to its reactivity and adaptability. Feedback reported by able-bodied subjects reveal a general tendency to favor soft interaction, i.e., low stiffness, which is perceived more human-like and comfortable. These combined results suggest the use of variable stiffness as a viable compromise between firm control and safe interaction which is worth investigating further.
Usability is one of the most important aspects of teleoperation. Ideally, the operator’s experience should be one of complete command over the remote environment, but also be as close as possible to what s/he would have if physically present at the remote end - i.e. transparency in terms of both action and perception. These two aspects may coincide in favorable conditions, where classic approaches such as the four-channel architecture ensures transparency of the control framework. In presence of substantial delays between the user and the slave, however, the stability-performance trade-off inherent to bilateral teleoperation deteriorates not only transparency, but also command. An alternative, unilateral approach is given by tele-impedance, which controls the slave-environment interaction by measuring and remotely replicating the user’s limb endpoint position and impedance. Not including force feedback to the operator, tele-impedance is absolutely robust to delays, while it completely lacks transparency.
This paper introduces a novel control framework which integrates a new, fully transparent, two-channel bilateral architecture with the tele-impedance paradigm. The result is a unified solution that mitigates problems of classical approaches, and provides the user with additional tools to modulate the slave robot’s physical interaction behavior, resulting in a better operator experience in spite of time inconsistencies. The validity and effectiveness of the proposed solution is demonstrated in terms of performance in the interaction tasks, of user fatigue and overall experience.
Summary This paper deals with the application of model predictive control (MPC) to optimize power flows in a network of interconnected microgrids (MGs). More specifically, a distributed MPC (DMPC) approach is used to compute for each MG how much active power should be exchanged with other MGs and with the outer power grid. Due to the presence of coupled variables, the DMPC approach must be used in a suitable way to guarantee the feasibility of the consensus procedure among the MGs. For this purpose, we adopt a tailored dual decomposition method that allows us to reach a feasible solution while guaranteeing the privacy of single MGs (ie, without having to share private information like the amount of generated energy or locally consumed energy). Simulation results demonstrate the features of the proposed cooperative control strategy and the obtained benefits with respect to other classical centralized control methods.
