A5042627597- Robotics and Sensor-Based Localization
- Robotic Path Planning Algorithms
- Advanced Vision and Imaging
- Image and Object Detection Techniques
- Wireless Body Area Networks
- Non-Invasive Vital Sign Monitoring
- 3D Surveying and Cultural Heritage
- Inertial Sensor and Navigation
- Indoor and Outdoor Localization Technologies
- Advanced Memory and Neural Computing
- Neuroscience and Neural Engineering
- Neural dynamics and brain function
Ministry of Education of the People's Republic of China
2018-2021
Huazhong University of Science and Technology
2018-2021
Adaptive Monte Carlo localization (AMCL) algorithm has a limited pose accuracy because of the nonconvexity laser sensor model, complex and unstructured features working environment, randomness particle sampling, final selection problem. In this paper, an improved AMCL is proposed, aiming to build radar‐based robot system in with LIDAR point cloud scan‐matching process after score calculating process. The weighted mean swarm used as initial scan matching matched probability grid map from...
In this work, a memristive circuit with affective multi-associative learning function is proposed, which mimics the process of human formation. It mainly contains three modules: associative learning, formation, expression. The first module composed several single-associative circuits consisting neurons and synapses. Memristive neuron will be activated output pulses if its input exceeds threshold. After it activated, can automatically return to inactive state. synapse realize forgetting...
Considering the adverse impact of speed measurement on accuracy pose estimation after a mobile robot slips, collides, or abducts, this paper proposes monocular inertial simultaneous localization and mapping algorithm that includes wheel anomaly detection. The adds to least squares problem in tightly coupled manner uses nonlinear optimization method maximize posterior probability solve optimal state estimation. For control Mecanum wheel, because existing closed-loop cannot calculate motion...
Currently, simultaneous localization and mapping (SLAM) is one of the main research topics in robotics field. Visual-inertia SLAM, which consists a camera an inertial measurement unit (IMU), can significantly improve robustness enable scale weak-visibility, whereas monocular visual SLAM scale-invisible. For ground mobile robots, introduction wheel speed sensor solve weak-visibility problem under abnormal conditions. In this paper, multi-sensor fusion algorithm using vision, inertia,...
The visual SLAM method is widely used for self-localization and mapping in complex environments. Visual-inertia SLAM, which combines a camera with IMU, can significantly improve the robustness enable scale weak-visibility, whereas monocular scale-invisible. For ground mobile robots, introduction of wheel speed sensor solve weak-visible problem under abnormal conditions. In this thesis, multi-sensor fusion algorithm using vision, inertia, measurements proposed. are combined tightly coupled...