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With the development of artificial intelligence, proximity sensors show their great potential in intelligent perception. This paper aims to propose a new planar capacitive sensor for the proximity sensing of a conductor.

Different from traditional structures, the proposed sensor is characterized by sawtooth-structured electrodes. A series of numerical simulations have been carried out to study the impact of different geometrical parameters such as the width of the main trunk, the width of the sawtooth and the number of sawtooths. In addition, the impact of the lateral offset of the approaching graphite block is investigated.

It is found that sensitivity is improved with the increase of the main trunk with, sawtooth width and sawtooth number while a larger lateral offset leads to a decrease in sensitivity. The performance of the proposed planar capacitive proximity sensor is also compared with two conventional planar capacitive sensors. The results show that the proposed planar capacitive sensor is obviously more sensitive than the two conventional planar capacitive sensors.

In this paper, a new planar capacitive sensor is proposed for the proximity sensing of a conductor. The results show that the capacitive sensor with the novel structure is obviously more sensitive than the traditional structures in the detection of the proximity conductor.

To solve the problem of low sensitivity of traditional capacitive proximity sensor, this paper aims to propose a novel capacitive sensor for detection of an approaching conductor.

Five capacitive proximity sensors with different structures are designed and the performance is compared with the traditional capacitive sensor. The impacts of geometrical parameters on the performance of the proposed capacitive sensor are studied. Furthermore, the sensitivity of the proposed capacitive sensor to an approaching conductor with different sizes is discussed. Also, how the designed capacitive sensor is sensitive to the lateral placement of the approaching object is analyzed.

Several capacitive proximity sensor structures have been designed and analyzed. It is found that the capacitive sensor with the top small ring-bottom large ring structure shows stronger electric field distribution around the top electrode and higher sensitivity to the approaching conductor than other sensors. Through further analysis of the proposed sensor, the results demonstrate that proposed capacitive sensor is effective for proximity object detection.

This paper proposes a novel capacitive proximity sensor with top small ring-bottom large ring structure. Compared with the traditional capacitive sensor, the proposed capacitive sensor is more sensitive to the approaching object. This would be helpful for the accurate detection of the approaching object. Also, the top and bottom electrodes are much smaller.

The purpose of this paper is to present a dual-mode proximity sensor composed of inductive and capacitive sensing modes, which can help the robot distinguish different objects and obtain distance information at the same time. A systematic study of sensor response to various objects and the function of cooperation sensing is needed. Furthermore, the application in the field of robotic area needs to be discussed.

Numerical modeling of each sensing modes and simulations based on finite element analysis method has been carried out to verify the designed dual-mode sensor. A number of objects composed of different materials are used to research the cooperation perception and proximity sensing functions. In addition, the proposed sensor is used on the palm of a mechanical hand as application experiment.

The characteristics of the sensor are summarized as follows: the sensing range of inductive mode is 0-5.6 mm for detecting a copper block and the perceive range of capacitive mode is 0-5.1 mm for detecting a plastic block. The collaborative perceive tests validated that the non-ferromagnetism metals can be distinguished by inductive mode. Correspondingly, ferromagnetism metals and dielectric objects are differentiated by capacitive mode. Application experiments results reveal that both plastic bottle and steel bottle could be detected and differentiated. The experimental results are in agreement with those of simulations.

This paper provides a study of dual-mode proximity sensor in terms of design, experiments and application.

Various types of sensors such as tactile, proximity and visual, have been developed to give robots flexibility and adaptability. It is argued that for complex tasks the individual sensors need to be integrated into a total system. In this article a variety of sensors developed by the authors are presented as modules and a design approach for a total system is discussed.

The purpose of this paper is to present the sensing mechanism, design issues, performance evaluation and applications for planar capacitive sensors. In the context of characterisation and imaging of a dielectric material under test (MUT), a systematic study of sensor modelling, features and design issues is needed. In addition, the influencing factors on sensitivity distribution, and the effect of conductivity on sensor performance need to be further studied for planar capacitive sensors.

While analytical methods can provide accurate solutions to sensors of simple geometries, numerical modelling is preferred to obtain sensor response to different design parameters and properties of MUT, and to derive the sensitivity distributions of various electrode designs. Several important parameters have been used to evaluate the response of the sensors in different sensing modes. The designs of different planar capacitive sensor arrays are presented and experimentally evaluated.

The response features and design guidelines for planar capacitive sensors in different sensing modes have been summarised, showing that the sensor in the transmission mode or the single‐electrode mode is suitable for material characterisation and imaging, while the sensor in the shunt mode is suitable for proximity/displacement measurement. The sensitivity distribution of the sensor depends largely on the geometry of the electrodes. Conductivity causes positive changes for the sensor in the transmission and single‐electrode mode, but negative changes for the sensor in the shunt mode. Experimental results confirm that sensing depths of the sensor arrays and the influence of buried conductor on capacitance measurements are in agreement with simulations.

Experimental verification is needed when a sensor is designed.

This paper provides a comprehensive study for planar capacitive sensors in terms of sensor design, evaluation and applications.

The purpose of this paper is to study the optimization of a pulsed-excitation gradiometric inductive sensing system.

The authors applied numerical finite-element modeling for the simulation of the step responses of different target materials to identify the particular contribution of the magnetic permeability and the electric conductivity. Four materials of technical importance (aluminum, copper, constructional steel and stainless steel) and four fictive test materials were modeled for the comparison of different materials possessing a wide range of combinations of material parameters. A microcontroller-based measurement setup was implemented for the qualitative validation of the simulation results. A simple signal processing chain was also applied for the time-domain conversion of the direct step response signals to increase the time scale of the signals to be processed by common mixed-signal components.

The step response signals contain relevant information of the target material quality and the sensor-to-target distance. The target materials can be distinguished and the sensor-target distance can be determined by the evaluation of the step response signals with an appropriate algorithm based on the measurement of the time and voltage of an extreme of the time dependent measurement signals. Both direct and time-domain converted signals can be used for material independent proximity sensing.

In order to design an inductive proximity switch, an evaluation method of the response signals has been proposed by using an analog RLC circuit. With the presented method, a target material invariant inductive proximity switch can be realized.

Drones are used in several purposes including examining areas, mapping surroundings and rescue mission operations. During these tasks, they could encounter compound surroundings having multiple obstacles, acute edges and deadlocks. The purpose of this paper is to propose an obstacle dodging technique required to move the drones autonomously and generate the obstacle's map of an unknown place dynamically.

Therefore, an obstacle dodging technique is essentially required to move autonomously. The automaton of drones requires complicated vision sensors and a high computing force. During this research, a methodology that uses two basic ultrasonic-oriented proximity sensors placed at the center of the drone and applies neural control using synaptic plasticity for dynamic obstacle avoidance is proposed. The two-neuron intermittent system has been established by neural control. The synaptic plasticity is used to find turning angles from different viewpoints with immediate remembrance, so it helps in decision-making for a drone. Hence, the automaton will be able to travel around and modify its angle of turning for escaping objects during the route in unknown surroundings with narrow junctions and dead ends. Furthermore, wherever an obstacle is detected during the route, the coordinate information is communicated using RESTful Web service to an android app and an obstacle map is generated according to the information sent by the drone. In this research, the drone is successfully designed and automated and an obstacle map using the V-REP simulation environment is generated.

Simulation results show that the drone effectively moves and turns around the obstacles and the experiment of using web services with the drone is also successful in generating the obstacle's map dynamically.

The obstacle map generated by autonomous drone is useful in many applications such as examining fields, mapping surroundings and rescue mission operations.

In advanced robotics applications in unstructured environments (e.g. those foreseen in space) some degree of dexterity and autonomy is necessary in order to safely and successfully execute the required tasks. With this respect, besides the kinematic configuration, important aspects to be considered in the design of robotic end‐effectors are the sensorial equipment and proper control strategies. In this paper, an activity for designing and experimenting a gripper for this operation in unstructured environments is reported, and laboratory results are presented and discussed.

Integration of lasers and fibre optics into robotic systems provides new opportunities in sensing and material processing. Increased productivity and application of robots in hostile environments are other possibilities.

Roger Main gives a four‐part report on the optical technologies which are playing an increasingly important role in sensor development.