本实验主要针对智能机器人定位建图与场景理解、运动规划、视觉伺服控制等方面展开研究，致力于无人平台的智能化与自主化，从而实现复杂、多样环境下的地面与空中机器人全自主导航。
1.无人平台定位建图与场景理解（Localization, Mapping, and Scene Understanding）
研究挑战：
定位建图与场景理解是无人平台进行自主作业的先决条件。在GPS拒止的复杂环境下进行机器人自主定位面临着定位漂移、场景退化等问题，为实现机器人全自主导航带来了巨大挑战。
最新成果：
[1]C. Li, X. Zhang*, H. Gao, R. Wang, Y. Fang. Bridging the gap between visual servoing and visual SLAM: a novel integrated interactive framework, IEEE Transactions on Automation Science and Engineering(T-ASE), 2022, 19(4): 2245-2255.
[2]H. Y. Liu, R. Song*, X. Zhang, H. Liu.Point clouds segmentation based on Euclidean clustering and multi-plane extraction in rugged field, Measurement Science and Technology, 2021, 32(9): 095106.
[3]J. Yuan, W. Zhu, X. Dong, F. Sun, X. Zhang, Q. Sun, Y. Huang. A novel approach to image-sequence-based mobile robot place recognition, IEEE Transactions on Systems, Man, and Cybernetics: Systems (T-SMCS), 2021, 51(9): 5377-5391.
[4]J. Yuan, J. Cai, X. Zhang, Q. Sun, F. Sun, W. Zhu. Fusing skeleton recognition with face-TLD for human following of mobile service robots, IEEE Transactions on Systems, Man and Cybernetics: Systems(T-SMCS), 2021, 51(5): 2963-2979.
[5]J. Jiang, J. Yuan, X.T. Zhang, X. Zhang. DVIO: An optimization-based tightly coupled direct visual-inertial odometry, IEEE Transactions on Industrial Electronics(T-IE), 2021, 68(11): 11212-11222.
[6]Q. Sun, J. Yuan, X. Zhang, F. Duan. Plane-Edge-SLAM: seamless fusion of planes and edges for SLAM in indoor environments, IEEE Transactions on Automation Science and Engineering(T-ASE), 2021, 18(4): 2061 - 2075.
[7]J. Wen,X. Zhang*, H. Gao, J. Yuan, Y. Fang. CAE-RLSM: consistent and efficient redundant line segment merging for online feature map building, IEEE Transactions on Instrumentation and Measurement(T-IM), 2020, 69(7): 4222-4237.
[8]F. Jiang, X. Zhang*, X. Chen, Y. Fang. Distributed optimization of visual sensor networks for coverage of a large-scale 3-D scene, IEEE/ASME Transactions on Mechatronics(T-MECH), 2020, 25(6): 2777-2788.
[9]H. Gao, X. Zhang*, J. Yuan, J. Song, Y. Fang.A novel global localization approach based on structural unit encoding and multiple hypothesis tracking, IEEE Transactions on Instrumentation and Measurement(T-IM), 2019, 68(11): 4427-4442.
[10]H. Gao, X. Zhang*, J. Wen, J. Yuan, Y. Fang, Autonomous indoor exploration via graph-based SLAM using directional endpoint features and polygon map construction, IEEE Transactions on Automation Science and Engineering(T-ASE), 2019, 16(4): 1531-1542.
实验视频：
2.无人平台运动规划（Motion planning and Autonomous Navigation）
研究挑战：
运动规划，是机器人以及先进机电系统学界的基础核心问题与关键共性技术。如何同时确保实时性、完整性与最优性仍是运动规划的一大难题。
最新成果：
[1]J. Wen, X. Zhang*, H. Gao, J. Yuan, and Y. Fang. E3MoP: efficient motion planning based on heuristic-guided motion primitives pruning and path optimization with sparse-banded structure, IEEE Transactions on Automation Science and Engineering(T-ASE), 2022, 19(4): 2762 – 2775.
[2]S. Zhang, X. Zhang*, T. Li, J. Yuan, and Y. Fang, Fast active aerial exploration for traversable path finding of ground robots in unknown environments, IEEE Transactions on Instrumentation & Measurement(T-IM), 2022, 71: 1-13.
[3]H. Wang, S. Zhang, X.Y. Zhang, X. Zhang*, and J. Liu. Near-optimal 3-D visual coverage for quadrotor UAVs under photogrammetric constraints, IEEE Transactions on Industrial Electronics(T-IE), 2022, 69(2): 1694-1704.
[4]P. Shen, X. Zhang*, Y. Fang, and M. Yuan. Real-time acceleration-continuous path-constrained trajectory planning with built-in tradeoff between cruise and time-optimal motions, IEEE Transactions on Automation Science and Engineering(T-ASE), 2020, 17(4): 1911-1924.
[5]X.T. Zhang, Y. Fang, X. Zhang, P. Shen, J. Jiang and X. Chen. Attitude-constrained time-optimal trajectory planning for rotorcrafts: theory and application to visual servoing, IEEE/ASME Transactions on Mechatronics(T-MECH), 2020, 25(4): 1912-1921.
[6]X. Zhang, J. Wang, Y. Fang, H. Gao, J. Yuan. Multilevel humanlike motion planning for mobile robots in complex indoor environments, IEEE Transactions on Automation Science and Engineering(T-ASE), 2019, 16(3): 1244-1258.
[7]P. Shen, X. Zhang*, and Y. Fang. Complete and time-optimal path-constrained trajectory planning with torque and velocity constraints: theory and applications, IEEE/ASME Transactions on Mechatronics(T-MECH), 2018, 23(2): 735-746.
[8]X. Zhang, Y. Fang, N. Sun. Minimum-time trajectory planning for underactuated overhead crane systems with state and control constraints. IEEE Transactions on Industrial Electronics(T-IE), 2014, 61(12): 6915-6925.
实验视频：
3.无人平台视觉伺服控制（Visual Servoing of Autonomous Systems）
研究挑战：
视觉系统所引入的不确定性，如位姿估计应用场景受限、深度信息未知、摄像机参数未知、摄像机视场角受限等,叠加移动机器人本身的非完整性运动学约束(早期经典的视觉伺服方法主要针对完整性约束工业机械臂)，给移动机器人位姿估计与视觉控制器的设计带来了巨大的挑战。
最新成果：
[1]C. Li,X. Zhang*, H. Gao, R. Wang, Y. Fang. Bridging the gap between visual servoing and visual SLAM: a novel integrated interactive framework, IEEE Transactions on Automation Science and Engineering(T-ASE), 2022, 19(4): 2245 – 2255.
[2]R. Wang,X. Zhang*, Y. Fang, and B. Li. Virtual-goal-guided RRT for visual servoing of mobile robots with FOV constraint, IEEE Transactions on Systems, Man and Cybernetics: Systems(T-SMCS), 2022, 52(4): 2073-2083.
[3]R. Wang,X. Zhang*, Y. Fang. Visual tracking of mobile robots with both velocity and acceleration saturation constraints, Mechanical Systems and Signal Processing(MSSP), 2021,150: 107274.
[4]X.T. Zhang, Y. Fang,X. Zhang, J. Jiang and X. Chen. Dynamic image-based output feedback control for visual servoing of multirotors, IEEE Transactions on Industrial Informatics(T-II), 2020, 16(12): 7624-7636.
[5]X.T. Zhang, Y. Fang,X. Zhang, J. Jiang and X. Chen. A novel geometric hierarchical approach for dynamic visual servoing of quadrotors, IEEE Transactions on Industrial Electronics(T-IE), 2020, 67(5): 3840-3849.
[6]X. Zhang, R. Wang, Y. Fang, B. Li, and B. Ma. Acceleration-level pseudo-dynamic visual servoing of mobile robots with backstepping and dynamic surface control, IEEE Transactions on Systems, Man and Cybernetics: Systems(T-SMCS), 2019, 49(10): 2071-2081.
[7]B. Li,X. Zhang*, Y. Fang, W. Shi. Visual servoing of wheeled mobile robots without desired images, IEEE Transactions on Cybernetics(T-CYBER), 2019, 49(8): 2835-2844.
[8]B. Li,X. Zhang*, Y. Fang, W. Shi. Visual servo regulation of wheeled mobile robots with simultaneous depth identification, IEEE Transactions on Industrial Electronics(T-IE), 2018, 65(1): 460-469.
[9]X. Zhang, Y. Fang, B. Li, J. Wang. Visual servoing of nonholonomic mobile robots with uncalibrated camera-to-robot parameters, IEEE Transactions on Industrial Electronics(T-IE), 2017, 64(1): 390-400.
[10]X. Zhang, Y. Fang, X. Liu. Motion-estimation-based visual servoing of nonholonomic mobile robots. IEEE Transactions on Robotics(T-RO), 2011, 27(6): 1167-1175.
实验视频：
