Prostate cancer is the second most common malignancy in American men. High-dose-rate brachytherapy is a popular treatment technique in which a large, localized radiation dose is used to kill cancer. Utilization of curvilinear catheter implantation inside the prostate gland to provide access channels to host the radiation source has shown superiority in terms of improved dosimetric constraints compared to straight needles. To this aim, we have introduced an active needle to curve inside the prostate conformal to the patient’s specific anatomical relationship for improved dose distribution to the prostate and reduced toxicity to the organs at risk. This work presents closed-loop control of our tendon-driven active needle in water medium and air using the position feedback of the tip obtained in real time from an ultrasound (US) or an electromagnetic (EM) tracking sensor, respectively. The active needle consists of a compliant flexure section to realize bending in two directions via actuation of two internal tendons. Tracking errors using US and EM trackers are estimated and compared. Results show that the bending angle of the active needle could be controlled using position feedback of the US or the EM tracking system with a bending angle error of less than 1.00 degree when delay is disregarded. It is concluded that the actuation system and controller, presented in this work, are able to realize a desired bending angle at the active needle tip with reasonable accuracy paving the path for tip tracking and manipulation control evaluations in a prostate brachytherapy.

Owing to inherent flexibility, compliant actuator with physical elastic elements can implement compliant interactions between robot and environment. Nonlinear stiffness elastic actuators (NSEAs) use one motor to adjust position and stiffness, which improve compactness of variable stiffness actuators, and consider high torque/force resolution and high bandwidth. The primary challenge of designing a NSEA is designing a reliable compliant mechanism with a given torque-deflection profile. In this study, a general design method of torsional compliant mechanism through given discrete torque-deflection points was proposed, where a chain algorithm based on 2R pseudo-rigid-body model was used to describe the large deformation in elastic elements. Moreover, the theoretical model of stiffness of a compliant mechanism based on series flexible beams was developed. Based on the proposed model, the dimensional parameters of proposed compliant mechanism were designed satisfying the condition of the given torque-deflection points. Finally, simulation and physical experiment of the designed compliant mechanism through three given torque-deflection points are conducted to show the effectiveness of the proposed method. The designed compliant mechanism was tested and evaluated in the self-developed NSEA.

We create a new tactile recording system with which we develop a three-axis fingernail-color sensor that can measure a three-dimensional force applied to fingertips by observing the change of the fingernail’s color. Since the color change is complicated, the relationships between images and three-dimensional forces were assessed using convolution neural network (CNN) models. The success of this method depends on the input data size because the CNN model learning requires big data. Thus, to efficiently obtain big data, we developed a novel measuring device, which was composed of an electronic scale and a load cell, to obtain fingernail images with 0$^\circ$ to 360$^\circ$ directional tangential force. We performed a series of evaluation experiments to obtain movies of the color changes caused by the three-axis forces and created a data set for the CNN models by transforming the movies to still images. Although we produced a generalized CNN model that can evaluate the images of any person’s fingernails, its root means square error (RMSE) exceeded both the whole and individual models, and the individual models showed the smallest RMSE. Therefore, we adopted the individual models, which precisely evaluated the tangential-force direction of the test data in an $F_x$-$F_y$ plane within around $\pm$2.5$^\circ$ error at the peak points of the applied force. Although the fingernail-color sensor possessed almost the same level of accuracy as previous sensors for normal-force tests, the present fingernail-color sensor acts as the best tangential sensor because the RMSE obtained from tangential-force tests was around 1/3 that of previous studies.

In mobile robot localization with multiple sensors, myriad problems arise as a result of inadequacies associated with each of the individual sensors. In such cases, methodologies built upon the concept of multisensor fusion are well-known to provide optimal solutions and overcome issues such as sensor nonlinearities and uncertainties. Artificial neural networks and fuzzy logic (FL) approaches can effectively model sensors with unknown nonlinearities and uncertainties. In this article, a robust approach for localization (positioning) of a mobile robot in indoor as well as outdoor environments is proposed. The neural network is utilized as a pseudo-sensor that models the global positioning system (GPS) and is used to predict the robot’s position in case of GPS signal loss in indoor environments. The data from proprioceptive sensors such as inertial sensors and GPS are fused using the Kalman and the complementary filter-based fusion schemes in the outdoor case. To eliminate the position inaccuracies due to wheel slippage, an expert FL system (FLS) is implemented and cascaded with the sensor fusion module. The proposed technique is tested both in simulation and in real scenarios of robot movements. The simulations and results from the experimental platform validate the efficacy of the proposed algorithm.

This paper deals with the robust force and position control problems of series elastic actuators (SEAs). It is shown that an SEA’s force control problem can be described by a second-order dynamic model which suffers from only matched disturbances. However, the position control dynamics of an SEA is of fourth order and includes matched and mismatched disturbances. In other words, an SEA’s position control is more complicated than its force control, particularly when disturbances are considered. A novel robust motion controller is proposed for SEAs by using disturbance observer (DOb) and sliding mode control. When the proposed robust motion controller is implemented, an SEA can precisely track desired trajectories and safely contact with an unknown and dynamic environment. The proposed motion controller does not require precise dynamic models of environments and SEAs. Therefore, it can be applied to many different advanced robotic systems such as compliant humanoids, industrial robots and exoskeletons. The validity of the proposed motion controller is experimentally verified.

For a real-time robotic prosthetic control, gait event detection plays an important role. In this paper, one novel sensor was proposed to realize gait event detection. The sensor includes one strain gauge bridge, which can reflect the entire deformation of carbon-fiber footplate on a robotic prosthesis. Three unilateral transtibial amputees participated in the experiments. Experimental results show that using the proposed sensor method, gait event detection (stance phase and swing phase) accuracy is approximately 100%. Based on the detected gait events, three locomotion modes (sit, stand, and walk) and the corresponding transition modes could be determined. Difference between different gait event detection systems was further conducted.

A comparison of series, parallel, and dual Passive Assist Devices(PADs) designed using energy minimization based on a known maneuver is presented. Implementation of a PAD can result in an improvement in system performance with respect to efficiency, reliability, and/or utility. We introduce a new initial design using a weighted force displacement curve fit. A robust design approach for a family of maneuvers is developed and presented. Applications to a 3-link manipulator arm show that PADs could reduce energy consumption between 60% and 80%.

The paper discusses the shape control problem related to a class of hyper-redundant robot arms with continuum elements, i.e. tentacle arms. A spatial weighted technique for sensor measurements is used in order to facilitate the parameter estimation. The paper focuses on the shape control by using the curvature gradient a constant parameter along the segment arm. The conditions that ensure a constant curvature gradient for a class of tentacle arms characterized by elastic backbone are determined. A sensor network distributed along the robot arm is used for the shape control. The main parameters of the arm shape, curvature and curvature gradient or “shape” Jacobian for the control problem are estimated. Two measuring systems are used: a) a distributed angle sensor network and b) a curvature sensor placed at the end of the arm segment. The stability analysis and the resulting controllers are obtained using the concept of boundary geometric control and the weighted state control methods. The shape control algorithms for dynamic models with uncertain components are proposed. Numerical simulations and experimental results illustrate the effectiveness of the above mentioned algorithms.

The increased use of unmanned aerial vehicles (UAVs) is coincidentally accompanied by a notable lack of sensors suitable for enabling further improvement in levels of autonomy and, consequently, integration into the National Airspace System (NAS). The majority of available sensors suitable for UAV integration into the NAS are based on infrared detectors, focal plane arrays, optical and ultrasonic rangefinders, etc. These sensors are generally not able to detect or identify other UAV-sized targets and, when detection is possible, considerable computational power is typically required for successful identification. Furthermore, the performance of visual-range optical sensor systems may suffer when operating under conditions that are typically encountered during search and rescue, surveillance, combat, and most other common UAV applications. However, the addition of a miniature RADAR sensor can, in consort with other sensors, provide comprehensive target detection and identification capabilities for UAVs. This trend is observed in manned aviation where RADAR sensors are the primary on-board detection and identification sensors. In this paper, a miniature, lightweight X-band RADAR sensor for use on a miniature (710-mm rotor diameter) rotorcraft is described. We present an analysis of the performance of the RADAR sensor in a realistic scenario with two UAVs. Additionally, an analysis of UAV navigation and collision avoidance behaviors is performed to determine the effect of integrating RADAR sensors into UAVs. Further study is also performed to demonstrate the scalability of the RADAR for use with larger UAV classes.

Existing sonar rings are limited in their refresh rate to the transmit echo rate, that is, waiting for maximum range echoes to arrive before transmitting again. This paper presents a sonar ring refreshing at 60 Hz for 5.7-m range, which is twice the transmit echo rate, and this leads to lower latency, denser measurements. Two custom Field Programmable Gate Array signal processors provide real time continuous match filtering with dynamic templates. A new method is implemented to select the transmit time from a random set based on minimizing interference. Experiments demonstrate the increased refresh rate, interference rejection, and maps generated by the sonar ring.

Matched filtering optimally estimates the arrival time for a sonar sensor by correlating received signals with templates. This paper presents a sonar ring with continuous matched filtering on 48 receiver channels sampled at 500kHz. The design dynamically switches the matched filter templates to account for pulse shape variations with range. To achieve real-time, low-latency and optimal performance, processing is implemented on an field-programmable gate array (FPGA) transmitting sonar pulses (2 periods of a 45kHz sine wave) at repetition rate of 30-Hz to 5.7-m range. The paper describes the removal of secondary peaks of the correlation output of matched filtering and template selection. Results include sonar maps, accuracy measurements and localization of weak targets.

A new type of 28-DOF (degree of freedom) full-size humanoid robot, driven by a closed-chain type of joint actuation system, is developed in this paper. Each leg of the robot is composed of six joints, where three are at the hip, one is at the knee, and two are at the ankle. The robot has six joints for each arm, one balancing joint, and three joints for the head, with two cameras. The weight of the robot is 75 kg, and its height is 168 cm.

The actuation systems of the pitching joint for the arms and legs of the robot are designed based on a closed-chain mechanism composed of four bar links driven by a ball screw, and each leg of the robot is designed to support 95 kg weight to include a 20 kg payload that can be carried by the robot arms having very light designs (with weight 8.5 kg), but each capable of carrying a 10 kg payload.

An analysis of the closed-chain joint actuation systems of a light arm capable of handling heavy objects is performed, and the light arm is designed via finite-element method analysis performed using ANSYS. In addition, the kinematic analysis and the detailed structure of the arm and leg of the robot are performed.

The main controller uses the ARM processor and a distributed controller for the leg joints is developed using the TMS320c2407 processor with the communications between the main and joint controllers being performed via the CAN system.

Good performances of the proposed robot is demonstrated by presenting several experimental results; these include (1) experimentally handling a 13 kg payload, (2) through walking experiments of the robot supporting a 85 kg load, and (3) measurements of the arm and leg joint motors while performing walking experiments.

To enhance tactile display capability, we performed a series of experiments based on psychophysics in which we adopted a circle and eight kinds of ovals as stimuli of the convex line (hereafter tactile image). The circle's diameter is 10 mm, the minor axes of the eight ovals are decreased in 3% steps from the circles, and each major axis is adjusted so that the area of each oval equals the circle area. Human subjects judged which stimuli (presented on the left or the right tactile images) equal the circle. The experiment was conducted on both the finger pads and the thenar parts to compare their experimental sensitivity ratios with the sensitivity ratio estimated on the basis of mechanoreceptor density. The discrimination sensitivity for the thenar part is inferior to that for the finger pad in terms of the low density of the mechanoreceptor in the thenar part. The tactile image was mainly recognized by a slowly adaptive type I unit, but the first adaptive type II unit was not affected by specimen cooling due to discrimination precision. Subsequently, discrimination sensitivity was not different between the free and restricted haptic motions. Since this result implies that the tactile image is modified by a motor signal for the haptic motion to prevent blurring of the tactile image, perhaps the motion movement in the tactile display is changed based on the design convenience.