Volumetric deep learning approach towards stereo matching aggregates a cost volume computed from input left and right images using 3D convolutions. Recent works showed that utilization of extracted image features and a spatially varying cost volume aggregation complements 3D convolutions. However, existing methods with spatially varying operations are complex, cost considerable computation time, and cause memory consumption to increase. In this work, we construct Guided Cost volume Excitation (GCE) and show that simple channel excitation of cost volume guided by image can improve performance considerably. Moreover, we propose a novel method of using top-k selection prior to soft-argmin disparity regression for computing the final disparity estimate. Combining our novel contributions, we present an end-to-end network that we call Correlate-and-Excite (CoEx). Extensive experiments of our model on the SceneFlow, KITTI 2012, and KITTI 2015 datasets demonstrate the effectiveness and efficiency of our model and show that our model outperforms other speed-based algorithms while also being competitive to other state-of-the-art algorithms. Codes will be made available at https://github.com/antabangun/coex.

Over the past decade, much research has been done to improve single‐fog images. However, most of these have concentrated on outdoor environments and little has been done for indoor environments. In this study, an effective method of removing fog from images both indoors and outdoors is presented. A new single image enhancement approach is based on mixture of dark channel prior (DCP) and contrast limited adaptive histogram equalisation with discrete wavelet transform (CLAHE‐DWT) algorithms. With the DCP algorithm using modified transmission map, the authors obtained fast processing speed and clean dehazed image without refining process. The CLAHE and DWT methods improved the contrast and sharpness of images. Finally, an enhanced image was produced by fusing the CLAHE and DWT images. To demonstrate the effectiveness of the proposed method, the authors performed objective image quality assessments, and so on. Through a variety of experiments for various indoor and outdoor images with fog, the proposed method was proven to be highly effective.

This paper presents a modified nonlinear pneumatic model for pneumatic force servo systems. The modified model is proposed in order to estimate pressures accurately for both chambers of a pneumatic cylinder by adopting flow coefficient maps, which is different from a conventional model whose flow coefficient is constant. The simulated data from the model is also compared to the experiment result and shows its accuracy compared to a widely used conventional model. The modified model and the experimental procedure are described and verified in this paper as well. Finally, the applicability of the proposed model to model-based controller design is also shown through the experiment of force servo controls based on a force sensor.

In this paper, we propose the novel gait trajectory adaptation method applicable to an exoskeleton for strength augmentation. The proposed method consists of the online positive feedback trajectory adaptation method and the swing phase duration adaptation method. The swing test results of an exoskeleton prototype showed that the proposed method is more adaptable to the change of the trajectory amplitude than the general trajectory control method mainly used for rehabilitation and it can adjust the swing phase duration as the walking speed changes. This method can be utilized to design the fast walking control of an exoskeleton in a swing phase.

In daily life, most hand movements involve the simultaneous activation of multiple fingers. Models generated by semiunsupervised learning in which only individual finger activation data are used in training have recently been suggested for simultaneous and proportional control of prosthetic robot hands. Although training with many datasets should be avoided, simultaneous activation data need to be used, for example, when the model estimation of the simultaneous activation is very poor or highly coupled among the degrees-of-freedoms (DOFs). In this paper, we propose a method for generating a model using any type of activation data (individual, simultaneous, or both) by modifying the nonnegative matrix factorization (NMF) with the Hadamard product (HP). The model provided by this method is called NMF-HP. NMF-HP has two advantages: First, it can use simultaneous activation data for training. Second, NMF-HP decouples coupled DOFs by forcing nonactive DOFs to be zero during the training phase. NMF-HP was tested in two cases (trained with only individual activation data and trained with both individual and simultaneous activation data) in offline and online experiments. In the offline test, NMF-HP outperformed the conventional semiunsupervised models for the simultaneous activation of the fingers. In the online test, NMF-HP was significantly better than NMF in the estimation of finger-motion intentions. This result contrasts with that of a previous study in which performance in the online test revealed a little difference between the models, possibly due to the human-embedded control. Thus, the result of this paper indicates that using simultaneous activation data and reducing the coupling among DOFs may be effective in enhancing the performance of the real-time control of a prosthetic robot hand.

Electrotactile stimulation has been used to provide sensory information of forearm prosthesis to users. Although conventional sensory feedback method, where one electrode expresses sensory information of only one finger, could provide force information of three fingers by using three electrodes, it showed less cognitive accuracy when more than two electrodes were stimulated simultaneously compared to individual stimulation. To improve the cognitive accuracy, we presented a sensory feedback method called two-channel electrotactile stimulation for the thumb, index and middle fingers using only two electrodes. The force information of the index and middle fingers was delivered into two electrodes, respectively, by intermittent stimulation. The information of the thumb was delivered to the user by inserting additional offset pulses onto the channel of the index finger based on an assumption that the force of thumb is proportional to the sum of the forces of the index and middle fingers. The presence of offset pulses in the channel indicates the binary state of thumb if it contacts with an object or not. We conducted two psychophysical experiments where healthy subjects classified the binary states of each finger and identified intensity from two-channel stimuli. The cognitive accuracies for intensity identification were 78.8% and 62.2% for the intermittent stimulation and conventional method, respectively, and accuracy for classifying the fingers was 93.1% for every combination of the three fingers. The results demonstrated that the proposed two-channel electrotactile stimulation could be an attractive method to express the information of fingers of prosthesis with high accuracy.

When designing a lower-limb assisting robot with body-weight support (BWS), it is important to achieve high force fidelity to support body weight at standing phase. Low impedance operation at swing phase is also required not to disturb leg motions for users. The SoftGait is designed to achieve both performances with a simple mechanical structure based on a pneumatic actuator and low cost sensor development. The SoftGait generates large force for body-weight-supporting in squatting mode corresponding to user's body weight. In fact, in walking mode, it enables a user to experience more comfortable walking with support from intrinsic compliance.

In this paper, a dual-mode twisting actuation mechanism with an active clutch is newly presented for a high performance tendon-driven robot (e.g., robot hand). This mechanism is a kind of mechanical automatic power transmission mechanism which provides fast motion and large contraction force by two geared motors. One of the motors is adopted for main actuation and the other is utilized for active clutch. The active clutch consisting of low-power DC motor and gear set allows easy control of the dual-mode twisting actuation and simplifies relaxation process of twisted strings which was a critical problem by a passive brake in previous research [17]. Kinematics of the proposed mechanism is represented and its simulation is performed to verify the performance numerically. By using BLDC & DC motor with 8 W & 0.3 W power, we developed a prototype of the dual-mode twisting actuation with the weight of 45.7 g and the size of 71 mm × 21.5 × 15 mm. Despite of simple structure, the proposed mechanism shows that operation mode-change can be easily managed and the relaxation time was much more reduced than that of the passive brake version.

In this paper, a method to extract the fingertip forces of the index and middle fingers from surface electromyography (sEMG) signals is studied by adopting the known common spatial pattern (CSP) approach. For unsupervised estimation of fingertip forces in real-time, CSP filtering is shown to be a notably effective method compared with known approaches for handling sEMG signals. The results of the proposed method are comparable to those of supervised estimations, such as linear regression and artificial neural network. The efficacy of the proposed method is validated by experiments.

Legged systems are potentially expected to have outstanding mobility. However, they have shown only modest levels of capability to traverse on flat ground. This paper introduces a biped robot inspired by the hind limbs of cats. We present the characteristics of the system and conduct a position analysis based on vector loop equations. Afterwards, the ground clearance and parallel movement of the robotic leg are shown. We present a speed equation in an effort to verify how the major parameters affect the speed. In addition, we explore control strategies for ground speed matching, acceleration, slip, and speed control. A dynamic simulation shows that the biped robot reached 13.31 leg lengths per second (9.3km/h). This biped robot with the speed equation and its control strategies allow us to understand legged locomotion and can show us how to improve the speed.

In this paper, the anthropomorphic robot hand is newly proposed by adopting dual-mode twisting actuation and EM joint locking mechanism. The proposed robot hand consists of five finger modules. Each finger has four links and three joints, and Joint 2 and 3 are coupled by the four-bar linkage mechanism. The dual-mode twisting actuation allows that the robot finger can move fast (up to 356.7 deg/sec) in Mode I and generate a large grasping force(up to 36.5 N) in Mode II. In addition, the workspace of the robot finger module is enlarged by EM joint locking mechanism depending on the locking states. In order to verify the effectiveness of the mechanisms adopted in the robot hand, we theoretically and numerically analyze the performances of the robot finger module such as bending speed, fingertip force, and workspace. Finally, through the developed robot hand, we perform the grasping test for various objects and the grasping performance is experimentally demonstrated.

In this paper, a pneumatic power generator based on the chemical reaction is newly proposed by using a small piston pump for the injection of the fuel. Based on the understanding of chemical reaction property, the piston pump is designed by crank-slider mechanism. The piston pump allows compact size and light weight of the entire power generation system compared to the conventional approaches using blow-down tank. In order to verify the effectiveness of the proposed power generation system, we theoretically and experimentally analyze the performance of the system. In addition, we realize the power generator and applies it to an underactuated robot finger for the feasibility test.

A dual-mode robot finger is proposed to achieve a high-speed motion and large grasping force with a single motor. The robot finger has two actuator modes, which consist of the speed mode and the force mode. Based on the geometric analysis of each mode, the main design parameters of the proposed robot finger are derived, and their effectiveness is verified by simulations. In addition, using experiments with a prototype of a robot finger, the validity of the proposed approach is demonstrated.