Proximity perception is a technology that has the potential to play an essential role in the future of robotics. It can fulfill the promise of safe, robust, and autonomous systems in industry and everyday life, alongside humans, as well as in remote locations in space and underwater. In this survey article, we cover the developments of this field from the early days up to the present, with a focus on human-centered robotics. In this domain, proximity sensors are typically deployed in two scenarios: first, on the exterior of manipulator arms to support safety and interaction functionality, and second, on the inside of grippers or hands to support grasping and exploration. Therefore, based on this observation, in the beginning of this article, we propose a categorization to organize the use cases of proximity sensors in human-centered robotics. Then, we devote effort to present the sensing technologies and different measuring principles that have been developed over the years, also providing a summary in form of a table. Following, we review the literature regarding the applications that have been proposed. Finally, we give an overview of the most important trends that will shape the future of this domain.

Optimization of coil sizes for wireless power transfer applications has a significant impact on the range and efficiency of the wireless power system. Often it is difficult to accurately analyze how a set of coils will perform before they are constructed due to the complexity of approximating the parasitic components and coupling coefficients associated with the coils. Also, for certain wireless power applications such as consumer electronic devices, implanted medical devices and industrial equipment that have physical constraints on the size and shape of the coils, it can be a difficult and time-consuming process to design and evaluate several different coil configurations for optimal range and efficiency. This paper provides simplified design equations to accurately calculate the self inductance, capacitance, resistance, quality factor and coupling coefficient in terms of coil geometries for flat, spiral coils. Experimental results validate the analysis and a design example is provided to optimize the size of a transmit coil for maximum range and wireless power efficiency to a 5.8cm receive coil used in a four-element wireless power transfer system.

Brain-computer interfaces (BCIs) are an emerging strategy for spinal cord injury (SCI) intervention that may be used to reanimate paralyzed limbs. This approach requires decoding movement intention from the brain to control movement-evoking stimulation. Common decoding methods use spike-sorting and require frequent calibration and high computational complexity. Furthermore, most applications of closed-loop stimulation act on peripheral nerves or muscles, resulting in rapid muscle fatigue. Here we show that a local field potential-based BCI can control spinal stimulation and improve forelimb function in rats with cervical SCI. We decoded forelimb movement via multi-channel local field potentials in the sensorimotor cortex using a canonical correlation analysis algorithm. We then used this decoded signal to trigger epidural spinal stimulation and restore forelimb movement. Finally, we implemented this closed-loop algorithm in a miniaturized onboard computing platform. This Brain-Computer-Spinal Interface (BCSI) utilized recording and stimulation approaches already used in separate human applications. Our goal was to demonstrate a potential neuroprosthetic intervention to improve function after upper extremity paralysis.

Acoustic traps and levitation systems can lift, translate and manipulate a wide range of objects and materials without contact. This enables new manipulation capabilities for robots that may not be possible otherwise. This paper presents an acoustic balance, a contactless method for weighing acoustically trapped objects in air. The method works by measuring a step response: the system commands a change in the phase of the acoustic emitters, which results in a sudden change in the equilibrium position of the trap. The object held within the acoustic trap undergoes damped oscillation as it settles into the new equilibrium point. The mass of the trapped object can be determined from the frequency of oscillation. Combined with methods for adding and merging materials in the trap, the method presented here can potentially enable a robot to operate a closed-loop process to acquire or maintain a desired quantity of material. Using weight as an error signal, material could be added by the acoustic system until the required quantity is in the trap.