The analytical formulation of piezoelectric flutter energy harvesting using a bistable material, while considering uncertainties in the model is presented in this paper. Bistable laminates provide the advantage of large deflection due to the nonlinear snap-through characteristics when exposed to external loading, and can therefore provide a suitable base for piezoelectric material in energy harvesting applications. A piezoelectric material that is bounded on the surface of bistable laminates, subjected to external loading, generates large strains and hence relatively higher electrical output energy, in comparison with the case where piezoelectric material is bonded on a regular surface, with analogous loading conditions. Although information regarding the external loading, material characteristics of the bistable laminate and the piezoelectric material, boundary conditions, and overall electrical circuit efficiency can be defined for analytical purposes, the exact model of the system is not readily accessible. The unavoidable uncertainties in the material, loading, and efficiency of a complex system call for a probabilistic approach. Hence, this paper provides a formulation that considers uncertainty bounds in obtaining a realistic model. Optimal Uncertainty Quantification (OUQ) is used in this paper, which takes into account uncertainty measures with optimal bounds and incomplete information about the system, as a well-defined optimization problem according to maximum probabilities, subjected to the imposed constraints. The OUQ allows the inspection of the solution for a span of uncertain input parameters, as a reliable and realistic model.

Visual servoying is an active and popular area of research among roboticists. Eventhough viual servo techniques enhance the perfomance, the associated systems still use traditional methods for their input control. Many research activities and applications have been carried out to implement effective and precise controlling of bilateral systems. This paper presents a 3D spresctroscope-based control technique for bilateral systems. The effectiveness of the available master side designs are evaluated against gesture-based techniques. Joystick control, Electromyography (EMG) ,Voice control, Haptic control, Exoskeleton control, Gesture and Brain Control Interface (BCI) are identified in the litreature as available bilateral inputs. In the present technnique, we have introduced Leap Motion Controller (LMC) to extrat the human hand gestures and their parameters. Then these parameters are convereted into respective joint sapce angles using the presented mathematical model. The mathematical models for fingertip mapping, inverse kinematics, dynamics and trajectory generation are implemented and studied. Wolfman Mathematica 10 and MATLAB simulation framework are used to validate the mathematical models, simulations and developed control algorithms. The developed system has sucesfully imitated the fingertip motion. In particular, the system has been able to imitate the figretip motion with a deviation of 6.7 % in X axis, 5.5% in Y axis and 7.9% in Z axis with respect to the expected position.

A subject who wears a suitable robotic device will be able to walk in complex environments with the aid of environmental recognition schemes that provide reliable prior information of the human motion intent. Researchers have utilized 1D laser signals and 2D depth images to classify environments, but those approaches can face the problems of self-occlusion. In comparison, 3D point cloud is more appropriate for depicting the environments. This paper proposes a directional PointNet to directly classify the 3D point cloud. First, an inertial measurement unit (IMU) is used to offset the orientation of point cloud. Then the directional PointNet can accurately classify the daily commuted terrains, including level ground, climbing up stairways, and walking down stairs. A classification accuracy of 98% has been achieved in tests. Moreover, the directional PointNet is more efficient than the previously used PointNet because the T-net, which is utilized to estimate the transformation of the point cloud, is not used in the present approach, and the length of the global feature is optimized. The experimental results demonstrate that the directional PointNet can classify the environments in robust and efficient manner.

Many animals possess actively movable tactile sensors in their heads, to explore the near-range space. During locomotion, an antenna is used in near range orientation, for example, in detecting, localizing, probing, and negotiating obstacles. A bionic tactile sensor used in the present work was inspired by the antenna of the stick insects. The sensor is able to detect an obstacle and its location in 3D (Three dimensional) space. The vibration signals are analyzed in the frequency domain using Fast Fourier Transform (FFT) to estimate the distances. Signal processing algorithms, Artificial Neural Network (ANN) and Support Vector Machine (SVM) are used for the analysis and prediction processes. These three prediction techniques are compared for both distance estimation and material classification processes. When estimating the distances, the accuracy of estimation is deteriorated towards the tip of the probe due to the change in the vibration modes. Since the vibration data within that region have high a variance, the accuracy in distance estimation and material classification are lower towards the tip. The change in vibration mode is mathematically analyzed and a solution is proposed to estimate the distance along the full range of the probe.

Due to the increasing commercial interest in autonomy and sustainability, this paper reviews and presents a comprehensive sum-mary of the resonant-inductive power transmission (RPT) technology for autonomous mobile robots. It outlines historic and recent research activities in wireless power transmission, covering the fundamental operation of microwave, capacitive and inductive power transfer technologies, state-of-the-art developments in RPT for high-power applications, current design and health standards, technological drawbacks, and possible future trends. In this paper, coupling-enhanced pad designs, adaptive tuning techniques, compensation network designs, and control techniques are explored. Major design issues such as coupling variation, frequency splitting, and bifurcation are reviewed. The difference between maximum power transfer and maximum energy efficiency is high-lighted. Human exposure guidelines are summarized from documentations provided by the Institute of Electrical and Electronics Engineers (IEEE) and the International Commission on Non-ionizing Radiation Protection (ICNIRP). Other standards like WPC’s Qi and Airfuel design standards are also summarized. Finally, the possible trends of the relevant research and development, partic-ularly dynamic charging, are discussed. The intention of this review is to encourage designs that will relieve robot operators of the burden of frequent manual recharging, and to reduce downtime and increase the productivity of autonomous mobile robots in industrial environments.

In the last decade, significant progress has been made in applying passive capsule endoscopes (CE) to medical diagnostics. However, disadvantages still need to be overcome for better utilization. A major challenge is to actively control the movement of the CE and provide real-time location information. This paper proposes a magnetic tracking method for CE driven by an external magnetic field that is generated by four sets of electromagnetic coils around the CE. The tracking method is based on a magnetic sensor array. The magnetic actuation constitutes three steps. First, the driving current from each coil is obtained according to the control requirement for a certain position and orientation. Second, the magnetic field that is generated by the driving current in the tracking space is estimated according to the magnetic field model. It can also be measured by Hall-effect sensors embedded in the position system. Third, the magnetic field generated by the CE is subtracted from the total magnetic field measured by the sensors, and then the magnetic position algorithm is applied. In the experiments, the positioning error is found to be within 5.6 mm and the orientation error is under 8.5°. The proposed localization method would be used for closed-loop control of CE to achieve better and safer performance.

This paper proposes a new concept of an actively-controlled wave energy converter for suppressing the pitch and roll motions of floating offshore wind turbines. The wave energy converter consists of several floating bodies that receive the wave energy, actuators that convert the wave energy into electrical energy and generate the mechanical forces, and rigid bars that connect the floating bodies and the wind turbine platform and deliver the actuator forces to the platform. The rotational torques that are required to minimize the platform pitch and roll motions are determined using a linear quadratic regulator. The torques determined in this manner are realized through the actuator forces that maximize the wave power capture as well. The performance of the proposed wave energy converter in simultaneously suppressing the platform pitch and roll motions and extracting the wave energy is validated through simulations.

Vibration-assisted machining (VAM) has the advantages of extending tool life, reducing cutting force and improving the surface finish. Implementation of vibration assistance with high frequency and amplitude is still a challenge, especially for a micro-milling process. In this paper, a new 2D vibration stage for vibration-assisted micro-milling is developed. The kinematics of the milling process with vibration assistance is modeled, and the effects of vibration parameters on the periodic tool-workpiece separation (TWS) is analyzed. The structure of the vibration stage is designed with flexure hinges, and two piezoelectric actuators are used to drive the stage in two directions. An amplifier is integrated into the vibration stage, and the dynamics of the whole vibration system are identified and analyzed. Micro-milling experiments are conducted to determine the effects of vibration assistance on cutting force and surface quality.

A novel wireless and passive surface acoustic wave (SAW) sensor is developed for measuring temperature and pressure. The sensor has two single-port resonators on a substrate. One resonator, acting as the temperature sensor, is located at the fixed end without pressure deformation, and the other one, acting as the pressure sensor, is located at the free end to detect pressure changes due to substrate deformation. Pressure at the free end bends the cantilever, causing a relative change in the acoustic propagation characteristics of the SAW traveling along the surface of the substrate and a relative change in the resonant frequency of the resulting signal. The temperature acts on the entire substrate, affecting the propagation speed of the SAW on the substrate and directly affecting the resonant frequency characteristic parameters. The temperature and pressure performance of this new antenna-connected sensor is tested by using a network analyzer, a constant temperature heating station, and a force gauge. A temperature sensitivity of 1.5015 kHz/°C and a pressure sensitivity of 10.6 kHz/gf at the ambient temperature have been observed by wireless measurements. This work should result in practical engineering applications for high-temperature devices.

This paper deals with instrumenting a mechatronic system, through the incorporation of suitable sensors, actuators, and other required hardware. Sensors (e.g., semiconductor strain gauges, tachometers, RTD temperature sensors, cameras, piezoelectric accelerometers) are needed to measure (sense) unknown signals and parameters of a system and its environment. The information acquired in this manner is useful in operating or controlling the system, and also in process monitoring; experimental modeling (i.e., model identification); product testing and qualification; product quality assessment; fault prediction, detection and diagnosis; warning generation; surveillance, and so on. Actuators (e.g., stepper motors, solenoids, dc motors, hydraulic rams, pumps, heaters/coolers) are needed to “drive” a plant. Control actuators (e.g., control valves) perform control actions, and in particular they drive control devices. Micro-electromechanical systems (MEMS) use microminiature sensors and actuators. MEMS sensors commonly use piezoelectric, capacitive, electromagnetic and piezoresistive principles. MEMS devices provide the benefits of small size and light weight (negligible loading errors), high speed (high bandwidth), and convenient mass-production (low cost). The process of instrumentation involves the identification of proper sensors, actuators, controllers, and signal modification/interface hardware, and software with respect to their functions, operation, parameters, ratings, and interaction with each other, so as to achieve the performance requirements of the overall system, and interfacing/integration/tuning of the selected devices into the system, for a given application. This paper presents the key steps of instrumenting a mechatronic system, in a somewhat general and systematic manner. Examples are described to illustrate several key procedures of instrumentation.