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- research-articleJuly 2024
Multi-agent cooperative strategy with explicit teammate modeling and targeted informative communication
AbstractThe mainstream Multi-Agent Reinforcement Learning (MARL) methods introduce the teammate modeling or the communication mechanism into Centralized Training Decentralized Execution (CTDE) paradigm, which can improve coordination performance. However,...
- research-articleNovember 2023
MS-IRTNet: Multistage information interaction network for RGB-T semantic segmentation
Information Sciences: an International Journal (ISCI), Volume 647, Issue CNov 2023https://doi.org/10.1016/j.ins.2023.119442AbstractThe complementary information from RGB and thermal images can remarkably boost semantic segmentation performance. Existing RGB-T segmentation methods usually use simple interaction strategies to extract complementary information from ...
- research-articleJuly 2022
Volumetric Instance-Level Semantic Mapping Via BlendMask
2022 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM)Jul 2022, Pages 374–379https://doi.org/10.1109/AIM52237.2022.9863340Advanced tasks such as planning and scene interaction for autonomous robots require a detailed instance-level semantic map of the environment. To this end, this paper proposes a new volumetric instance-level semantic mapping approach, in which BlendMask ...
- research-articleDecember 2021
2D Topological Map Building by UAVs for Ground Robot Navigation
2021 IEEE International Conference on Robotics and Biomimetics (ROBIO)Dec 2021, Pages 663–668https://doi.org/10.1109/ROBIO54168.2021.9739395In air-ground cooperation, unmanned aerial vehicles (UAVs) are used to build a priori map of the ground environment from an aerial perspective, which is conducive to improve the navigation ability of ground robots. This paper proposes a 2D topology map ...
- ArticleOctober 2021
A “Look-Backward-and-Forward” Adaptation Strategy of NN Model Parameters for Prediction of Motion Trajectory
Intelligent Robotics and ApplicationsOct 2021, Pages 714–724https://doi.org/10.1007/978-3-030-89092-6_65AbstractPrediction of human motion trajectory is crucial for safe human-robot collaboration (HRC). The existing prediction method based on the adaptive neural network (NN) model couples the parameter estimation error with the priori estimation error of ...
- ArticleDecember 2020
Deep Point Cloud Odometry: A Deep Learning Based Odometry with 3D Laser Point Clouds
Advances in Neural Networks – ISNN 2020Dec 2020, Pages 154–163https://doi.org/10.1007/978-3-030-64221-1_14AbstractDeep learning-based methods have attracted more attention to the pose estimation research that plays a crucial role in location and navigation. How to directly predict the pose from the point cloud in a data-driven way remains an open question. In ...
- research-articleJuly 2020
A Hybrid Analytical and Data-driven Modeling Approach for Calibration of Heavy-duty Cartesian Robot*
2020 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM)Jul 2020, Pages 1286–1291https://doi.org/10.1109/AIM43001.2020.9158827Robot calibration is to enhance absolute positioning accuracy within robotic task space. Traditional method is to build the geometric error model and identify the deviation of kinematic parameters. In this paper, a hybrid analytical and data-driven non-...
- research-articleSeptember 2015
Contextual classification of 3D laser points with conditional random fields in urban environments
2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)Sep 2015, Pages 3908–3913https://doi.org/10.1109/IROS.2015.7353927Online 3D point cloud classification and scene understanding are crucial tasks for Unmanned Ground Vehicles (UGVs) equipped with multiple laser scanners. Due to the poor performance of traditional 2D image representation model for 3D point clouds, a novel ...
- research-articleDecember 2013
Path Planning in Complex 3D Environments Using a Probabilistic Roadmap Method
International Journal of Automation and Computing (SPIJAC), Volume 10, Issue 6Dec 2013, Pages 525–533https://doi.org/10.1007/s11633-013-0750-9AbstractThis paper presents a 3D path planning algorithm for an unmanned aerial vehicle (UAV) in complex environments. In this algorithm, the environments are divided into voxels by octree algorithm. In order to satisfy the safety requirement of the UAV, ...
- articleMay 2011
Reliable H∞ control for discrete uncertain time-delay systems with randomly occurring nonlinearities: the output feedback case
International Journal of Systems Science (IJSS), Volume 42, Issue 5May 2011, Pages 809–820https://doi.org/10.1080/00207721.2010.487950This article is concerned with the reliable H∞ output feedback control problem against actuator failures for a class of uncertain discrete time-delay systems with randomly occurred nonlinearities (RONs). The failures of actuators are quantified by a ...
- articleApril 2011
Reliable H∞ filtering for discrete time-delay systems with randomly occurred nonlinearities via delay-partitioning method
Signal Processing (SIGN), Volume 91, Issue 4April, 2011, Pages 713–727https://doi.org/10.1016/j.sigpro.2010.07.018In this paper, the reliable H"~ filtering problem is investigated for a class of uncertain discrete time-delay systems with randomly occurred nonlinearities (RONs) and sensor failures. RONs are introduced to model a class of sector-like nonlinearities ...
- research-articleJanuary 2010
Robust Adaptive Tracking Control for Nonlinear Systems Based on Bounds of Fuzzy Approximation Parameters
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans (TSMCPA), Volume 40, Issue 1January 2010, Pages 170–184https://doi.org/10.1109/TSMCA.2009.2030164A robust adaptive fuzzy control approach is developed for a class of multi-input-multi-output (MIMO) nonlinear systems with modeling uncertainties and external disturbances by using both the approximation property of the fuzzy logic systems and the ...
- ArticleOctober 2006
Robust Adaptive Neural Network Control for a Class of Nonlinear Systems
ISDA '06: Proceedings of the Sixth International Conference on Intelligent Systems Design and Applications - Volume 01October 2006, Pages 101–106https://doi.org/10.1109/ISDA.2006.232In this paper, a stable robust adaptive control approach is presented for a class of unknown nonlinear systems in the strict-feedback form with disturbances. The key assumption is that neural network approximation errors and external disturbances ...