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Robot trajectories comparison: a statistical approach.

Ansuategui A, Arruti A, Susperregi L, Yurramendi Y, Jauregi E, Lazkano E, Sierra B - ScientificWorldJournal (2014)

Bottom Line: Given an initial set of features, it automatically selects the most significant ones and performs a statistical comparison using them.Additionally, a graphical data visualization named polygraph which helps to better understand the obtained results is provided.The proposed method has been applied, as an example, to compare two different motion planners, FM(2) and WaveFront, using different environments, robots, and local planners.

View Article: PubMed Central - PubMed

Affiliation: Autonomous and Smart Systems Unit, IK4 Tekniker, Eibar, Spain.

ABSTRACT
The task of planning a collision-free trajectory from a start to a goal position is fundamental for an autonomous mobile robot. Although path planning has been extensively investigated since the beginning of robotics, there is no agreement on how to measure the performance of a motion algorithm. This paper presents a new approach to perform robot trajectories comparison that could be applied to any kind of trajectories and in both simulated and real environments. Given an initial set of features, it automatically selects the most significant ones and performs a statistical comparison using them. Additionally, a graphical data visualization named polygraph which helps to better understand the obtained results is provided. The proposed method has been applied, as an example, to compare two different motion planners, FM(2) and WaveFront, using different environments, robots, and local planners.

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The angle areas used for data collection.
© Copyright Policy - open-access
Related In: Results  -  Collection


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fig3: The angle areas used for data collection.

Mentions: It seems logical to characterize the trajectories using the data provided by the sensors on the robot. In the experiment performed, we use a laser device as leading sensor for the navigation system, and hence the laser readings are used for comparison purposes. First of all, four different regions of the laser reading area were defined (see Figure 3):


Robot trajectories comparison: a statistical approach.

Ansuategui A, Arruti A, Susperregi L, Yurramendi Y, Jauregi E, Lazkano E, Sierra B - ScientificWorldJournal (2014)

The angle areas used for data collection.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4262753&req=5

fig3: The angle areas used for data collection.
Mentions: It seems logical to characterize the trajectories using the data provided by the sensors on the robot. In the experiment performed, we use a laser device as leading sensor for the navigation system, and hence the laser readings are used for comparison purposes. First of all, four different regions of the laser reading area were defined (see Figure 3):

Bottom Line: Given an initial set of features, it automatically selects the most significant ones and performs a statistical comparison using them.Additionally, a graphical data visualization named polygraph which helps to better understand the obtained results is provided.The proposed method has been applied, as an example, to compare two different motion planners, FM(2) and WaveFront, using different environments, robots, and local planners.

View Article: PubMed Central - PubMed

Affiliation: Autonomous and Smart Systems Unit, IK4 Tekniker, Eibar, Spain.

ABSTRACT
The task of planning a collision-free trajectory from a start to a goal position is fundamental for an autonomous mobile robot. Although path planning has been extensively investigated since the beginning of robotics, there is no agreement on how to measure the performance of a motion algorithm. This paper presents a new approach to perform robot trajectories comparison that could be applied to any kind of trajectories and in both simulated and real environments. Given an initial set of features, it automatically selects the most significant ones and performs a statistical comparison using them. Additionally, a graphical data visualization named polygraph which helps to better understand the obtained results is provided. The proposed method has been applied, as an example, to compare two different motion planners, FM(2) and WaveFront, using different environments, robots, and local planners.

Show MeSH