Improved Path Planning for Indoor Patrol Robot Based on Deep Reinforcement Learning

To solve the problems of poor exploration ability and convergence speed of traditional deep reinforcement learning in the navigation task of the patrol robot under indoor specified routes, an improved deep reinforcement learning algorithm based on Pan/Tilt/Zoom(PTZ) image information was proposed in this paper. The obtained symmetric image information and target position information are taken as the input of the network, the speed of the robot is taken as the output of the next action, and the circular route with boundary is taken as the test. The improved reward and punishment function is designed to improve the convergence speed of the algorithm and optimize the path so that the robot can plan a safer path while avoiding obstacles first. Compared with Deep Q Network(DQN) algorithm, the convergence speed after improvement is shortened by about 40%, and the loss function is more stable.

Airborne SAR Radiometric Calibration Based on Improved Sliding Window Integral Method

To verify the performance of the high-resolution fully polarimetric synthetic aperture radar (SAR) sensor carried by the Xinzhou 60 remote-sensing aircraft, we used corner reflectors to calibrate the acquired data. The target mechanism in high-resolution SAR images is more complex than it is in low-resolution SAR images, the impact of the point target pointing error on the calibration results is more obvious, and the target echo signal of high-resolution images is more easily affected by speckle noise; thus, more accurate extraction of the point target position and the response energy is required. To solve this problem, this paper introduces image context information and proposes a method to precisely determine the integration region of the corner reflector using sliding windows based on the integral method. The validation indicates that the fully polarimetric SAR sensor on the Xinzhou 60 remote-sensing aircraft can accurately reflect the radiometric characteristics of the ground features and that the integral method can obtain more stable results than the peak method. The sliding window allows the position of the point target to be determined more accurately, and the response energy extracted from the image via the integral method is closer to the theoretical value, which means that the high-resolution SAR system can achieve a higher radiometric calibration accuracy. Additionally, cross-validation reveals that the airborne SAR images have similar quality levels to Sentinel-1A and Gaofen-3 images.

Speech recognition with a hearing-aid processing scheme combining beamforming with mask-informed speech enhancement

A signal processing approach combining beamforming with mask-informed speech enhancement was assessed by measuring sentence recognition in listeners with mild-to-moderate hearing impairment in adverse listening conditions that simulated the output of behind-the-ear hearing aids in a noisy classroom. Two types of beamforming were compared: binaural, with the two microphones of each aid treated as a single array, and bilateral, where independent left and right beamformers were derived. Binaural beamforming produces a narrower beam, maximising improvement in signal-to-noise ratio (SNR), but eliminates the spatial diversity that is preserved in bilateral beamforming. Each beamformer type was optimised for the true target position and implemented with and without additional speech enhancement in which spectral features extracted from the beamformer output were passed to a deep neural network trained to identify time-frequency regions dominated by target speech. Additional conditions comprising binaural beamforming combined with speech enhancement implemented using Wiener filtering or modulation-domain Kalman filtering were tested in normally-hearing (NH) listeners. Both beamformer types gave substantial improvements relative to no processing, with significantly greater benefit for binaural beamforming. Performance with additional mask-informed enhancement was poorer than with beamforming alone, for both beamformer types and both listener groups. In NH listeners the addition of mask-informed enhancement produced significantly poorer performance than both other forms of enhancement, neither of which differed from the beamformer alone. In summary, the additional improvement in SNR provided by binaural beamforming appeared to outweigh loss of spatial information, while speech understanding was not further improved by the mask-informed enhancement method implemented here.

Path Selection for the Inspection Robot by m-Generalized q-Neutrosophic PROMETHEE Approach

Path planning can be considered the most vital task of the autonomous robot. In this task, selecting an optimal route from the starting to the target position becomes an important problem that must be addressed when multiple competing optimization priorities are considered. Thus, a novel route assessment strategy based on a multi-criteria decision-making approach is proposed. The m-generalized q-neutrosophic PROMETHEE (PROMETHEE-mGqNS) method is applied to aggregate the competing route assessment requirements and choose an optimal route. A case study is investigated to explain the proposed strategy for path planning in a typical environment and indicates the method stability when incomplete input data characteristics are present.

Efficient Computation for Localization and Navigation System for a Differential Drive Mobile Robot in Indoor and Outdoor Environments

Numerous challenges are usually faced during the design and development of an autonomous mobile robot. Path planning and navigation are two significant areas in the control of autonomous mobile robots. The computation of odometry plays a major role in developing navigation systems. This research aims to develop an effective method for the computation of odometry using low-cost sensors, in the differential drive mobile robot. The controller acquires the localization of the robot and guides the path to reach the required target position using the calculated odometry and its created new two-dimensional mapping. The proposed method enables the determination of the global position of the robot through odometry calibration within the indoor and outdoor environment using Graphical Simulation software.

Improvement of the Transglycosylation Efficiency of a Lacto-N-Biosidase from Bifidobacterium bifidum by Protein Engineering

The lacto-N-biosidase LnbB from Bifidobacterium bifidum JCM 1254 was engineered to improve its negligible transglycosylation efficiency with the purpose of enzymatically synthesizing lacto-N-tetraose (LNT; Gal-β1,3-GlcNAc-β1,3-Gal-β1,4-Glc) in one enzymatic step. LNT is a prebiotic human milk oligosaccharide in itself and constitutes the structural core of a range of more complex human milk oligosaccharides as well. Thirteen different LnbB variants were expressed and screened for transglycosylation activity by monitoring transglycosylation product formation using lacto-N-biose 1,2-oxazoline as donor substrate and lactose as acceptor substrate. LNT was the major reaction product, yet careful reaction analysis revealed the formation of three additional LNT isomers, which we identified to have a β1,2-linkage, a β1,6-linkage, and a 1,1-linkage, respectively, between lacto-N-biose (Gal-β1,3-GlcNAc) and lactose. Considering both maximal transglycosylation yield and regioselectivity as well as minimal product hydrolysis, the best variant was LnbB W394H, closely followed by W465H and Y419N. A high transglycosylation yield was also obtained with W394F, yet the substitution of W394 and W465 of the subsite −1 hydrophobic platform in the enzyme with His dramatically impaired the undesirable product hydrolysis as compared to substitution with Phe; the effect was most pronounced for W465. Using p-nitrophenyl-β-lacto-N-bioside as donor substrate manifested W394 as an important target position. The optimization of the substrate concentrations confirmed that high initial substrate concentration and high acceptor-to-donor ratio both favor transglycosylation.

Swing control for a three-link brachiation robot based on sliding-mode control on irregularly distributed bars

The bionic-gibbon robot is a popular bionic robot. The bionic-gibbon robot can imitate a gibbon in completing brachiation motion between branches. With nonlinear and underactuated properties, the robot has important research value. This paper designs a type of bionic-gibbon robot with three links and two grippers. To simplify the controller, a plane control model is proposed, and its dynamic model is established. The control strategy in this paper divides the brachiation motion into several processes: adjust posture, open the gripper, the swing process and close the gripper. Based on sliding-mode control (SMC), the control method for the swing process is designed. The target position of the brachiation motion is set as the origin of the sliding-mode surface. In a finite time, the robot will reach the target position along the approach rate we adopt. In this way, the robot can complete the desired brachiation motion only by setting the position parameters of the target bar. We perform some simulations in ROS-Gazebo. The simulation results show that the bionic-gibbon robot can complete continuous brachiation motion on irregularly distributed bars. The sliding-mode control and the three-link structure significantly improve the robustness and swing efficiency of the bionic-gibbon robot.

Tracking Filter for Radio Surveillance upon UAV Detection

Unsanctioned intrusion of unmanned aerial vehicle (UAV) on the territory of the guarded object is primarily detected by specialized radio surveillance systems. The results obtained by radio surveillance systems are used for aiming of UAV visual identification and radio jamming systems. In this work, the problems of UAV detection and tracking of the target trajectory are considered. The known tracking filter systems for radio surveillance application were analyzed and a specialized matrix tracking filter system was proposed, which uses in its algorithm a dynamically changing energy potential of the radio surveillance system. The developed tracking filter system efficiency is evaluated using methods of matrix calculation, mathematical modeling, and probability theory. It has been established that the developed tracking filter system lets the radio surveillance equipment most effectively initiate trajectories of UAV, set its movement window, consider radio surveillance equipment characteristics, and approximate the trajectory of UAV at times of missed detections connected to radar cross-section fluctuations of moving targets. A high efficiency of the developed system has been achieved by decreasing the inaccuracy of the target position prediction two times in comparison with the known tracking filter systems. The obtained results allow easy scaling of the developed tracking filter system for its application as a part of any radio surveillance system.

Smart handheld device with flexible wrist and electrical bioimpedance sensor for tissue inspection

With the evolving demands of surgical intervention, there is a strong need for smaller and functionally augmented instruments to improve surgical outcomes, operational convenience, and diagnostic safety. Owing to the narrow and complicated anatomy, the probe head of the medical instrument is required to possess both good maneuverability and compact size. In addition, the development of medical instrument is moving toward patient-specialized, of which the articulation positions can be customized to reach the target position. To fulfill these requirements, this study presents the design of a smart handheld device which equips with a low cost, easy control, disposable flexible wrist, and an electrical bioimpedance sensor for medical diagnosis. Prototype of the device is made and tested. The experimental results demonstrate that the proposed device can provide accurate manipulation and effective tissue detection, showing a great potential in various medical applications.