The propagation of Internet-of-Things (IoT) sensors aboard moving objects has led to continuous spatiotemporal data streams that demand on-device, low-latency analysis. However, the underlying systems for processing this streaming data are ill-prepared. On the one hand, common stream processing engines lack support for spatiotemporal operations. On the other hand, existing libraries for spatiotemporal data are optimized for historical data rather than real-time processing. To bridge this gap, we present MobilityNebula, an integration between MEOS (Mobility Engine Open Source), a lightweight C library for spatiotemporal data management, and NebulaStream, a stream processing system designed for the edge-fog-cloud continuum. We evaluated MobilityNebula by deploying the system on edge devices, ingesting data from the Belgian railway operator (SNCB) trains, and performing real-time geospatial processing for point-based queries.

Robotic engineers face major challenges to solve the complex actuation needs of Human-Robot Collaboration with existing act robotic gearboxes. Available technologies comprise high-ratio Planetary Gearheads, Cycloid Drives and Harmonic Drives, inherited from conventional industrial robotics. Alternative approaches include Direct-Drive and Quasi Direct-Drive actuation strategies, which propose to cancel or substantially reduce gear ratio, in order to minimize reflected inertia and attain enough backdrivability for collaborative tasks. This paper presents the proof-of-concept validation of a novel high-ratio, Wolfrom-based, gearbox technology that follows a different approach to attain the same objective. Testing five different gearbox prototypes, we confirm the ability of the R2poweR technology to improve efficiency and backdrivability while retaining the weight and control advantages derived from the use of high reduction ratios. The result is a highly efficient, backdrivable, high-ratio gearbox with exciting Huma-Robot Collaboration potential.

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.

On novel actuator research in the field of cellular muscle-inspired actuators, skeletal muscles are often used as inspiration due to their modular and compact design and seemingly effortless control. Amongst others, the remaining challenges to tackle are robust designs, energy consumption minimization and control strategies. We have developed a discrete muscle-inspired actuator, in which solenoids can be overpowered and locked to recruit springs in series. This paper describes the spring and electronics design and proposes a binary actuator segmentation for increased resolution. Next, we propose and simulate a control strategy based on a lookup table, to cope with multiple discrete inputs, uni-directional force inputs and solenoid cooling time. Currently, the actuation units and springs are modular and can be tailored easily for specific applications. The resolution is maximized without under utilization of the actuator's capabilities, and our control strategy can currently control 12 motor units in real-time, which can be increased to 30. The experiments confirm the working of the control strategy.