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您的检索式：作者名="Shoukun Xu"
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| 1 | High-adaption locomotion with stable robot body for planetary exploration robot carrying potential instruments on unstructured terrain显示文摘There is a strong demand for Planetary Exploration Mobile robots(PEMRs)that have the capability of the traversability,stability,efficiency and high load while tackling the specialized tasks on planet surface.In this paper,an electric parallel wheel-legged hexapod robot which has high-adaption locomotion on the unstructured terrain is presented.Also,the hybrid control framework,which enables robot to stably carry the heavy loads as well as to traverse the uneven terrain by utilizing both legged and wheeled locomotion,is also proposed.Based on this framework,robot controls the multiple DOF leg for performing high-adaption locomotion to negotiate obstacles via Gait Generator(GG).Additionally,by using Whole-Body Control(WBC)of framework,robot has the capability of flexibly accommodating the uneven terrain by Attitude Control(AC)kinematically adjusting the length of legs like an active suspension system,and by Force/torque Balance Control(FBC)equally distributing the Ground Reaction Force(GRF)to maintain a stable body.The simulation and experiment are employed to validate the proposed framework with the physical system in the planetary analog environments.Particularly,to smoothly demonstrate the performance of robot transporting heavy loads,the experiment of carrying 3-person load of about 240 kg is deployed. | Kang XU Shoukun WANG Junzheng WANG Xiuwen WANG Zhihua CHEN Jinge SI | 2021 | Chinese Journal of Aeronautics2021，34，5： | 3 |
| 2 | Part-Whole Relational Few-Shot 3D Point Cloud Semantic Segmentation显示文摘This paper focuses on the task of few-shot 3D point cloud semantic segmentation.Despite some progress,this task still encounters many issues due to the insufficient samples given,e.g.,incomplete object segmentation and inaccurate semantic discrimination.To tackle these issues,we first leverage part-whole relationships into the task of 3D point cloud semantic segmentation to capture semantic integrity,which is empowered by the dynamic capsule routing with the module of 3D Capsule Networks(CapsNets)in the embedding network.Concretely,the dynamic routing amalgamates geometric information of the 3D point cloud data to construct higher-level feature representations,which capture the relationships between object parts and their wholes.Secondly,we designed a multi-prototype enhancement module to enhance the prototype discriminability.Specifically,the single-prototype enhancement mechanism is expanded to the multi-prototype enhancement version for capturing rich semantics.Besides,the shot-correlation within the category is calculated via the interaction of different samples to enhance the intra-category similarity.Ablation studies prove that the involved part-whole relations and proposed multi-prototype enhancement module help to achieve complete object segmentation and improve semantic discrimination.Moreover,under the integration of these two modules,quantitative and qualitative experiments on two public benchmarks,including S3DIS and ScanNet,indicate the superior performance of the proposed framework on the task of 3D point cloud semantic segmentation,compared to some state-of-the-art methods. | Shoukun Xu Lujun Zhang Guangqi Jiang Yining Hua Yi Liu | 2024 | Computers, Materials & Continua2024，78，3： | 0 |
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