Adaptive boundary-following algorithm guided by artificial potential field for robot navigation

Charifa, Samer; Bikdash, Marwan

doi:10.1109/riiss.2009.4937904

Cited by 11 publications

(8 citation statements)

References 29 publications

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“…The past literature on wall-following robots is vast, however we can immediately distinguish this work from potential-field approaches [17], [18], which need a priori knowledge about the environment, as well as from approaches based on mapping [19], [20], which require more sophisticated sensors than assumed here and need relatively high computational power and memory. We want to restrict attention to the so-called "reactive" or "feedback" [21] paradigm of robot control, where the task is specified as a dynamical relation instead of a prescribed plan.…”

Section: A Brief Survey Of Prior Literaturementioning

confidence: 99%

Toward dynamical sensor management for reactive wall-following

Koditschek

2013

2013 IEEE International Conference on Robotics and Automation

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We propose a new paradigm for reactive wallfollowing by a planar robot taking the form of an actively steered sensor model that augments the robot's motion dynamics. We postulate a foveated sensor capable of delivering third-order infinitesimal (range, tangent, and curvature) data at a point along a wall (modeled as an unknown smooth plane curve) specified by the angle of the ray from the robot's body that first intersects it. We develop feedback policies for the coupled (point or unicycle) sensorimotor system that drive the sensor's foveal angle as a function of the instantaneous infinitesimal data, in accord with the trade-off between a desired standoff and progress-rate as the wall's curvature varies unpredictably in the manner of an unmodeled noise signal. We prove that in any neighborhood within which the thirdorder infinitesimal data accurately predicts the local "shape" of the wall, neither robot will ever hit it. We empirically demonstrate with comparative physical studies that the new active sensor management strategy yields superior average tracking performance and avoids catastrophic collisions or wall losses relative to the passive sensor variant. Abstract-We propose a new paradigm for reactive wallfollowing by a planar robot taking the form of an actively steered sensor model that augments the robot's motion dynamics. We postulate a foveated sensor capable of delivering third-order infinitesimal (range, tangent, and curvature) data at a point along a wall (modeled as an unknown smooth plane curve) specified by the angle of the ray from the robot's body that first intersects it. We develop feedback policies for the coupled (point or unicycle) sensorimotor system that drive the sensor's foveal angle as a function of the instantaneous infinitesimal data, in accord with the trade-off between a desired standoff and progress-rate as the wall's curvature varies unpredictably in the manner of an unmodeled noise signal. We prove that in any neighborhood within which the thirdorder infinitesimal data accurately predicts the local "shape" of the wall, neither robot will ever hit it. We empirically demonstrate with comparative physical studies that the new active sensor management strategy yields superior average tracking performance and avoids catastrophic collisions or wall losses relative to the passive sensor variant.

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Section: A Brief Survey Of Prior Literaturementioning

confidence: 99%

Toward dynamical sensor management for reactive wall-following

Koditschek

2013

2013 IEEE International Conference on Robotics and Automation

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“…22, does not have a smooth variation outside the target region. In [23], we proposed the Harmonic Field with Optimized Boundary Conditions (HFOBC) combined with Boundary Following Algorithm (BFA) [24]. The HFOBC abandons the uniformity of boundary conditions used in the regular harmonic field, Eq.…”

Section: − →mentioning

confidence: 99%

Motion Planning of a Snake-Like Robot Using an Optimized Harmonic Potential Field

Charifa

Bikdash

2010

Paladyn, Journal of Behavioral Robotics

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Snake-like robots have gained popularity in the last three decades for their ability to utilize several gaits in order to navigate through di erent terrains. They are analogous in morphology to snakes, tentacles, and elephant trunks. We propose a novel method of navigating a snake-like robot based on the Harmonic Field with Optimized Boundary Conditions (HFOBC) and a boundary following algorithm. We apply the HFOBC navigation function using a number of fictitious charges equally spaced on each link. These charges actively follow the potential field towards the target. Futhermore, a generalized mathematical model for an n-link snake-like robot based on Lagrange formulation has also been proposed in this paper.

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“…Boundary following has also been investigated in robotics, but the models considered in this field are generally deterministic and are therefore less adequate for describing animal behavior (see Ref. [38] and references therein). Therefore, rather than by the boundary-following literature, our approach is inspired by models used for studying bacteria, cells, or animals moving up a stimulus gradient (e.g., a chemical gradient for Escherichia coli bacteria [39], the slime mold Dictyostelium discoideum and leukocytes [40,41], an electrical gradient for kertinocytes involved in wound healing [42], or a prey gradient in prey-predator models for some protozoa [43]).…”

Section: Introductionmentioning

confidence: 99%

Residence times and boundary-following behavior in animals

et al. 2014

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Many animals in heterogeneous environments bias their trajectories displaying a preference for the vicinity of boundaries. Here we propose a criterion, relying on recent invariance properties of residence times for microreversible Boltzmann's walks, that permits detecting and quantifying boundary-following behaviors. On this basis we introduce a boundary-following model that is a nonmicroreversible Boltzmann's walk and that can represent all kinds of boundary-following distributions. This allows us to perform a theoretical analysis of field-resolved boundary following in animals. Two consequences are pointed out and are illustrated: A systematic procedure can now be used for extraction of individual properties from experimental field measurements, and boundary-curvature influence can be recovered as an emerging property without the need for individuals perceiving the curvature via complex physiological mechanisms. The presented results apply to any memoryless correlated random walk, such as the run-and-tumble models that are widely used in cell motility studies.

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Adaptive boundary-following algorithm guided by artificial potential field for robot navigation

Cited by 11 publications

References 29 publications

Toward dynamical sensor management for reactive wall-following

Toward dynamical sensor management for reactive wall-following

Motion Planning of a Snake-Like Robot Using an Optimized Harmonic Potential Field

Residence times and boundary-following behavior in animals

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