This paper proposed a novel wireless location algorithm based on distance geometry （DG） constraint filtering for the time of arrival （TOA） of the signal （namely as DG-TOA）. Filtering and processing of the observ...This paper proposed a novel wireless location algorithm based on distance geometry （DG） constraint filtering for the time of arrival （TOA） of the signal （namely as DG-TOA）. Filtering and processing of the observed data and leading to the mathematical formulas based on DG-TOA algorithm are applied to location, also play crucial rules. Simulation results show that the proposed DG-TOA algorithm can provide more valid observation data and be more precise than least square estimate （LSE） algorithm in dense, multi-route, indoor circumstances with the ranging estimation error.展开更多
Visual tracking and grasping of moving object is a challenging task in the field of robotic manipulation,which also has great potential in applications such as human-robot collaboration.Based on the particle filtering...Visual tracking and grasping of moving object is a challenging task in the field of robotic manipulation,which also has great potential in applications such as human-robot collaboration.Based on the particle filtering framework and position-based visual servoing,this paper proposes a new method for visual tracking and grasping of randomly moving objects.A geometric particle filter tracker is established for visual tracking.In order to deal with the tracking efficiency issue for particle filter,edge detection and morphological dilation are employed to reduce the computation burden of geometric particle filtering.Meanwhile,the HSV image feature is employed instead of the grayscale feature to improve the tracking algorithm’s robustness to illumination change.A grasping strategy combining tracking and interception is adopted along with the position-based visual servoing(PBVS)method to achieve stable grasp of the target.Comprehensive comparisons on open source dataset and a large number of experiments on real robot system are conducted,which demonstrate the proposed method has competitive performance in random moving object tracking and grasping.展开更多
基金supported by the open research fund of National Mobile Communications Research Laboratory (W200906)the Fundamental Research Funds for the Central Universities (2009JBM012)
文摘This paper proposed a novel wireless location algorithm based on distance geometry （DG） constraint filtering for the time of arrival （TOA） of the signal （namely as DG-TOA）. Filtering and processing of the observed data and leading to the mathematical formulas based on DG-TOA algorithm are applied to location, also play crucial rules. Simulation results show that the proposed DG-TOA algorithm can provide more valid observation data and be more precise than least square estimate （LSE） algorithm in dense, multi-route, indoor circumstances with the ranging estimation error.
基金supported in part by the National Natural Science Foundation of China(Grant Nos.91748204,51905183,91948301)China Postdoctoral Science Foundation(Grant No.2018M642820)。
文摘Visual tracking and grasping of moving object is a challenging task in the field of robotic manipulation,which also has great potential in applications such as human-robot collaboration.Based on the particle filtering framework and position-based visual servoing,this paper proposes a new method for visual tracking and grasping of randomly moving objects.A geometric particle filter tracker is established for visual tracking.In order to deal with the tracking efficiency issue for particle filter,edge detection and morphological dilation are employed to reduce the computation burden of geometric particle filtering.Meanwhile,the HSV image feature is employed instead of the grayscale feature to improve the tracking algorithm’s robustness to illumination change.A grasping strategy combining tracking and interception is adopted along with the position-based visual servoing(PBVS)method to achieve stable grasp of the target.Comprehensive comparisons on open source dataset and a large number of experiments on real robot system are conducted,which demonstrate the proposed method has competitive performance in random moving object tracking and grasping.
