The Experts below are selected from a list of 53220 Experts worldwide ranked by ideXlab platform

Jianzhong Tang - One of the best experts on this subject based on the ideXlab platform.

  • A Hybrid Path Planning Algorithm for Unmanned Surface Vehicles in Complex Environment With Dynamic Obstacles
    IEEE Access, 2019
    Co-Authors: Zheng Chen, Youming Zhang, Yougong Zhang, Jianzhong Tang
    Abstract:

    Unmanned surface vesssel (USV) has been widely applied due to its advantages in the military reconnaissance and resources exploration. Path planning is one of the critical issues for USV applications, which usually includes global and local path planning methods. However, individual global path planning algorithms may not be easy to detect the dynamic obstacles in the Environment, and individual local path planning algorithms may not always guarantee the existence of the feasible solution for the Complex Environment. Therefore, a hybrid algorithm which effectively combines global and local path planning is proposed in this paper to overcome these drawbacks. The A* algorithm is used in the global path planning to generate a global path for USV to reach the target point. The dynamic window algorithm (DWA) is used in the local path planning to avoid the dynamic obstacles and track the global path by following the local target point which is the intersection of the global and local path planning. The weight coefficient considering sea state is added in the objective function of DWA, where the security of USV can be guaranteed by reducing the weight of velocity and increasing the weight of distance when the sea state level becomes high. Thus, USV can get a global optimal path and reach the target point in Complex Environment with dynamic obstacles and ocean currents via the proposed hybrid algorithm, and the comparative simulation is carried out to verify the effectiveness and advantage of the proposed method.

Zheng Chen - One of the best experts on this subject based on the ideXlab platform.

  • A Hybrid Path Planning Algorithm for Unmanned Surface Vehicles in Complex Environment With Dynamic Obstacles
    IEEE Access, 2019
    Co-Authors: Zheng Chen, Youming Zhang, Yougong Zhang, Jianzhong Tang
    Abstract:

    Unmanned surface vesssel (USV) has been widely applied due to its advantages in the military reconnaissance and resources exploration. Path planning is one of the critical issues for USV applications, which usually includes global and local path planning methods. However, individual global path planning algorithms may not be easy to detect the dynamic obstacles in the Environment, and individual local path planning algorithms may not always guarantee the existence of the feasible solution for the Complex Environment. Therefore, a hybrid algorithm which effectively combines global and local path planning is proposed in this paper to overcome these drawbacks. The A* algorithm is used in the global path planning to generate a global path for USV to reach the target point. The dynamic window algorithm (DWA) is used in the local path planning to avoid the dynamic obstacles and track the global path by following the local target point which is the intersection of the global and local path planning. The weight coefficient considering sea state is added in the objective function of DWA, where the security of USV can be guaranteed by reducing the weight of velocity and increasing the weight of distance when the sea state level becomes high. Thus, USV can get a global optimal path and reach the target point in Complex Environment with dynamic obstacles and ocean currents via the proposed hybrid algorithm, and the comparative simulation is carried out to verify the effectiveness and advantage of the proposed method.

Feng Zhang - One of the best experts on this subject based on the ideXlab platform.

  • A novel adaptive algorithm for location based on Distance-Loss model in Complex Environment
    2016 IEEE 20th International Conference on Computer Supported Cooperative Work in Design (CSCWD), 2016
    Co-Authors: Hao Fang, Fei Li, Weiming Shen, Feng Zhang
    Abstract:

    Location based services are the hottest applications on mobile device nowadays. Indoor wireless position is the key technology to enable location based service to work well indoors, where Global Position System normally couldn't work. The main tendency of indoor wireless position is based on Bluetooth and RSSI (radio signal strength indicator). RSSI is the key parameter for wireless position. But values of RSSI are affected by Environment factors easily. Because of this reason, results got from the indoor location technology are usually imprecise and unacceptable. In this paper, an adaptive algorithm based on Distance-Loss model in Complex Environment is introduced to deal with such problems. The algorithm makes the model adapt to the Environment by several parameters which are not influenced by Environment. The stability and the accuracy of the algorithm is evidenced by a series of strict experiences.

  • Research on obstacle avoidance control for multi-mobile robots formation in Complex Environment
    Proceedings of the World Congress on Intelligent Control and Automation (WCICA), 2010
    Co-Authors: Feng Zhang, Zhe Sun, Meiju Liu
    Abstract:

    This paper presents a new obstacle avoidance control method for multi-mobile robots formation in Complex Environment. At first, the formation based on the methods of leader-follower and artificial potential is built for multi-mobile robots; And then, the leader robot avoids obstacles autonomously, the follower robots track the leader robot, and detect obstacles by the sensors and then avoid obstacles; At last, the robots formation arrived their goal after avoiding obstacles and resuming their formation. The simulation results proved that the presented method is valid.

Nobuto Matsuhira - One of the best experts on this subject based on the ideXlab platform.

  • Basic Experiments for a Remote Control Robot-Mapping System in Complex Environment
    2019 IEEE International Conference on Mechatronics and Automation (ICMA), 2019
    Co-Authors: Li Ke, Tingxin Song, Nattawat Pinrath, Nobuto Matsuhira
    Abstract:

    Simultaneous localization and mapping (SLAM) constitutes the core challenge in autonomous navigation while avoiding obstacles for mobile robots. Traditional robots require close-range operators during mapping, and remote control remains difficult in a Complex Environment. Furthermore, the height of sensors limits the detection of small obstacles in 2D mapping. This paper presents a robot system that solves these problems. The system operates SLAM remotely, navigates narrow paths, and estimates the location of small obstacles beyond the detection range of 2D lidar. The experiments utilized the Robot Operating System and an open source GMapping software package. Lidar, a camera, and an inertial measurement sensor unit enabled the remote monitoring of the robot in real-time via Rivz, Rqt, and V-rep. Experiment results demonstrate the advantageous operability and reliability of the system.

Noh-hoon Myung - One of the best experts on this subject based on the ideXlab platform.

  • A Hybrid UTD-ACGF Technique for DOA Finding of Receiving Antenna Array on Complex Environment
    IEEE Transactions on Antennas and Propagation, 2015
    Co-Authors: Ji-hoon Park, Noh-hoon Myung
    Abstract:

    When a receiving antenna array operates on a Complex Environment, the ideal phase differences of the receiving voltages of the antenna array are significantly distorted by both mutual coupling and platform scattering. This distortion causes performance degradation of the direction of arrival (DOA) algorithms. For estimating and compensating for the phase distortion, an analysis of the receiving voltages of the receiving antenna array on the platform is required. In this paper, we propose a hybrid UTD-ACGF technique for modeling port voltages of the receiving antenna array on a Complex Environment. The Complex Environment is modeled by UTD technique, and the antenna array is modeled by ACGF. In order to explain the coupling effect between the Complex Environment and the antenna array, we use the first perturbation series approximation based on the exact mutual coupling perturbation series. The hybrid UTD-ACGF results are verified through comparison to MoM results. Finally, we statistically define a distortion matrix that has a relation between the distorted port voltages and the ideal port voltages. The distorted port voltages are evaluated using the hybrid UTD-ACGF technique as a backbone. In order to enhance the performance of the DOA algorithm, we efficiently estimate and compensate for the distortion matrix. A DOA simulation using the MUSIC algorithm is performed to confirm the compensatory effect of the distortion matrix.