The fate of the litter of dominant vegetation(willows and reeds) is one of the aspects studied in the frame of the project “Onderzoek Milieu Effecten Sigmaplan”. One of the questions to be considered is how long the...The fate of the litter of dominant vegetation(willows and reeds) is one of the aspects studied in the frame of the project “Onderzoek Milieu Effecten Sigmaplan”. One of the questions to be considered is how long the litter stays within the estuary. In this paper, the time the leaf litter(Salix triandra and Phragmites australis) stayed in the Schelde estuary was studied by using plant pigment as biomarkers with HPLC application. After analyzing the original data from the incubation experiment described by Dubuison and Geers(1999), the decomposition dynamics patterns of pigments were analyzed and described, and these decomposition dynamics patterns were used as calibration patterns. By using Spearman Rank Order Correlation, the calibration patterns of the pigments which were significant(p<0.05) were grouped. In this way, several groups of the calibration patterns of pigment decomposition were achieved. The presence or absence of these groups of pigments (whether they can be detected or not from HPLC) was shown to be useful in determining the time the litter has stayed in the water. Combining data of DW and POC, more precise timing can be obtained.展开更多
Articulated movements are fundamental in many human and robotic tasks.While humans can learn and generalise arbitrarily long sequences of movements,and particularly can optimise them to ft the constraints and features...Articulated movements are fundamental in many human and robotic tasks.While humans can learn and generalise arbitrarily long sequences of movements,and particularly can optimise them to ft the constraints and features of their body,robots are often programmed to execute point-to-point precise but fxed patterns.This study proposes a new approach to interpreting and reproducing articulated and complex trajectories as a set of known robot-based primitives.Instead of achieving accurate reproductions,the proposed approach aims at interpreting data in an agent-centred fashion,according to an agent s primitive movements.The method improves the accuracy of a reproduction with an incremental process that seeks frst a rough approximation by capturing the most essential features of a demonstrated trajectory.Observing the discrepancy between the demonstrated and reproduced trajectories,the process then proceeds with incremental decompositions and new searches in sub-optimal parts of the trajectory.The aim is to achieve an agent-centred interpretation and progressive learning that fts in the frst place the robots capability,as opposed to a data-centred decomposition analysis.Tests on both geometric and human generated trajectories reveal that the use of own primitives results in remarkable robustness and generalisation properties of the method.In particular,because trajectories are understood and abstracted by means of agent-optimised primitives,the method has two main features: 1) Reproduced trajectories are general and represent an abstraction of the data.2) The algorithm is capable of reconstructing highly noisy or corrupted data without pre-processing thanks to an implicit and emergent noise suppression and feature detection.This study suggests a novel bio-inspired approach to interpreting,learning and reproducing articulated movements and trajectories.Possible applications include drawing,writing,movement generation,object manipulation,and other tasks where the performance requires human-like interpretation and generalisation capabilities.展开更多
文摘The fate of the litter of dominant vegetation(willows and reeds) is one of the aspects studied in the frame of the project “Onderzoek Milieu Effecten Sigmaplan”. One of the questions to be considered is how long the litter stays within the estuary. In this paper, the time the leaf litter(Salix triandra and Phragmites australis) stayed in the Schelde estuary was studied by using plant pigment as biomarkers with HPLC application. After analyzing the original data from the incubation experiment described by Dubuison and Geers(1999), the decomposition dynamics patterns of pigments were analyzed and described, and these decomposition dynamics patterns were used as calibration patterns. By using Spearman Rank Order Correlation, the calibration patterns of the pigments which were significant(p<0.05) were grouped. In this way, several groups of the calibration patterns of pigment decomposition were achieved. The presence or absence of these groups of pigments (whether they can be detected or not from HPLC) was shown to be useful in determining the time the litter has stayed in the water. Combining data of DW and POC, more precise timing can be obtained.
基金supported by European Community s Seventh Framework Programme FP7/2007-2013,Challenge 2,Cognitive Systems,Interaction,Robotics(No.248311AMARSi)
文摘Articulated movements are fundamental in many human and robotic tasks.While humans can learn and generalise arbitrarily long sequences of movements,and particularly can optimise them to ft the constraints and features of their body,robots are often programmed to execute point-to-point precise but fxed patterns.This study proposes a new approach to interpreting and reproducing articulated and complex trajectories as a set of known robot-based primitives.Instead of achieving accurate reproductions,the proposed approach aims at interpreting data in an agent-centred fashion,according to an agent s primitive movements.The method improves the accuracy of a reproduction with an incremental process that seeks frst a rough approximation by capturing the most essential features of a demonstrated trajectory.Observing the discrepancy between the demonstrated and reproduced trajectories,the process then proceeds with incremental decompositions and new searches in sub-optimal parts of the trajectory.The aim is to achieve an agent-centred interpretation and progressive learning that fts in the frst place the robots capability,as opposed to a data-centred decomposition analysis.Tests on both geometric and human generated trajectories reveal that the use of own primitives results in remarkable robustness and generalisation properties of the method.In particular,because trajectories are understood and abstracted by means of agent-optimised primitives,the method has two main features: 1) Reproduced trajectories are general and represent an abstraction of the data.2) The algorithm is capable of reconstructing highly noisy or corrupted data without pre-processing thanks to an implicit and emergent noise suppression and feature detection.This study suggests a novel bio-inspired approach to interpreting,learning and reproducing articulated movements and trajectories.Possible applications include drawing,writing,movement generation,object manipulation,and other tasks where the performance requires human-like interpretation and generalisation capabilities.