Information Acquisition in the Exploration of Random Fields

Baillieul, John; Baronov, Dimitar

doi:10.1007/978-3-642-11278-2_1

Cited by 5 publications

(7 citation statements)

References 19 publications

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“…Part of the work in this paper has appeared in our previous papers [10] and [11]. Here, we extend this work to present a unified library of control laws that can provide the building blocks for complex strategies for monitoring and exploring potential fields, such as the ones presented in [8], [12], and a major companion paper [13].…”

Section: Introductionmentioning

confidence: 87%

A Motion Description Language for Robotic Reconnaissance of Unknown Fields

Baronov

Baillieul

2011

European Journal of Control

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Section: Introductionmentioning

confidence: 87%

A Motion Description Language for Robotic Reconnaissance of Unknown Fields

Baronov

Baillieul

2011

European Journal of Control

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“…Otherwise, κ k+1 is negative. 5 Building on Andersson's smooth trajectory [11], a novel trajectory is introduced in figure 2, which is constructed in two parts: (a) a sine-curve to send the tip towards the sample contour to allow the measuring of points on the contour; (b) a cosine-curve to move away from the contour, thus, avoiding the crossing of the sample when a point on the contour is measured. For any instant s 1 , s 2 , …, where r d (s i ) describes a point on the contour, the tip trajectory is defined by…”

Section: Andersson's Non-raster Scanning Methods and A Trajectory For...mentioning

confidence: 99%

An adaptive non-raster scanning method in atomic force microscopy for simple sample shapes

Zhang

Hatano

Tien

et al. 2015

Meas. Sci. Technol.

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It is a significant challenge to reduce the scanning time in atomic force microscopy while retaining imaging quality. In this paper, a novel non-raster scanning method for high-speed imaging is presented. The method proposed here is developed for a specimen with the simple shape of a cell. The image is obtained by scanning the boundary of the specimen at successively increasing heights, creating a set of contours. The scanning speed is increased by employing a combined prediction algorithm, using a weighted prediction from the contours scanned earlier, and from the currently scanned contour. In addition, an adaptive change in the height step after each contour scan is suggested. A rigorous simulation test bed recreates the x–y specimen stage dynamics and the cantilever height control dynamics, so that a detailed parametric comparison of the scanning algorithms is possible. The data from different scanning algorithms are compared after the application of an image interpolation algorithm (the Delaunay interpolation algorithm), which can also run on-line.

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“…Here, however, the description of the topology is defined in the context of the data acquisition particulars of the search process. In [13], we have introduced the related notion of a monotone search sequence. These concepts and their relationship to reconnaissance decisions will be discussed in what follows.…”

Section: Topology Of a Scalar Potential Fieldmentioning

confidence: 99%

“…Second, we solve the problem in terms of binary decision making. Binary decisions and more specifically the exploration vs. exploitation paradigm have been investigated extensively both in the context of search by humans [11], and search by automata [12], [13]. The framework allows us to investigate the ways that groups and individuals actually make decisions in various settings and how these decisions compare with what would be optimal in some sense.…”

Section: Introductionmentioning

confidence: 99%

Topology guided search of potential fields

Baronov

Baillieul

2010

49th IEEE Conference on Decision and Control (CDC)

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Using reactive control algorithms and a dictionary of motion primitives, we have developed search and reconnaissance protocols for mobile robots aimed at efficiently discovering key features of an unknown potential field's topology (as opposed to its geometry). This work has in a natural way led to the creation of parsimonious reconnaissance routines that do not rely on any prior knowledge about the environment. The design of topology guided search protocols uses a mathematical framework that quantifies the relationship between what is discovered and what remains to be discovered. This quantification rests on an information theory inspired model, whose properties allow us to treat search as a problem in optimal information acquisition. The main idea is that "conservative" and "aggressive" search strategies can be precisely defined, and search decisions regarding exploration vs. exploitation choices can be informed by our information-like metric.

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Information Acquisition in the Exploration of Random Fields

Cited by 5 publications

References 19 publications

A Motion Description Language for Robotic Reconnaissance of Unknown Fields

A Motion Description Language for Robotic Reconnaissance of Unknown Fields

An adaptive non-raster scanning method in atomic force microscopy for simple sample shapes

Topology guided search of potential fields

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