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Static force field representation of environments based on agents nonlinear motions

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Damian Campo, Alejandro Betancourt, Lucio Marcenaro, Carlo Regazzoni

Machine Learning · Submitted 9 Sep 2019

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim The proposed approach is first evaluated on synthetic data; posteriorly, the method is applied on real trajectories coming from moving pedestrians in an indoor environment.

how it is stated · asserted 0.99 read the record →

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arXiv ID1909.04010 (version 1)
Pith IDYTFOKUXX, Pith's permanent record of this paper and its review
CitationAlejandro Betancourt, Carlo Regazzoni, Damian Campo, Lucio Marcenaro. "Static force field representation of environments based on agents nonlinear motions." arXiv:1909.04010 (2019). https://pith.science/paper/YTFOKUXX
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The compiled record

The paper's own sentences, arranged. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.

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Compiled by classifier-1.13.0 via TypeSafe API, question bank abstract-p1-20260923, 2026-09-23: 1 request, 6,074 input tokens.

What the abstract itself states, as probabilities: claims first 0.04 · states limitation 0.09 · human participants 0.52 · controlled comparison 0.03 · randomized assignment 0.01 · states quantitative result 0.03 · compares with prior results 0.07 · mentions code or data availability 0.02.

The abstract, sentence by sentence

arXiv listing abstract v1. Results and the main claim are underlined; .

This paper presents a methodology that aims at the incremental representation of areas inside environments in terms of attractive forces. It is proposed a parametric representation of velocity fields ruling the dynamics of moving agents. It is assumed that attractive spots in the environment are responsible for modifying the motion of agents. A switching model is used to describe near and far velocity fields, which in turn are used to learn attractive characteristics of environments. The effect of such areas is considered radial over all the scene. Based on the estimation of attractive areas, a map that describes their effects in terms of their localizations, ranges of action, and intensities is derived in an online way. Information of static attractive areas is added dynamically into a set of filters that describes possible interactions between moving agents and an environment. The proposed approach is first evaluated on synthetic data; posteriorly, the method is applied on real trajectories coming from moving pedestrians in an indoor environment.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 This paper presents a methodology that aims at the incremental representation of areas inside environments in terms of attractive forces. contribution 1.00 0.85 0.12 asserted 0.98
s1 It is proposed a parametric representation of velocity fields ruling the dynamics of moving agents. method 0.66 0.75 0.05 asserted 0.95
s2 It is assumed that attractive spots in the environment are responsible for modifying the motion of agents. method 0.70 0.13 0.04 asserted 0.97
s3 A switching model is used to describe near and far velocity fields, which in turn are used to learn attractive characteristics of environments. method 0.99 0.70 0.05 asserted 1.00
s4 The effect of such areas is considered radial over all the scene. method 0.97 0.36 0.04 asserted 0.99
s5 Based on the estimation of attractive areas, a map that describes their effects in terms of their localizations, ranges of action, and intensities is derived in an online way. method 0.67 0.91 0.27 asserted 1.00
s6 Information of static attractive areas is added dynamically into a set of filters that describes possible interactions between moving agents and an environment. method 0.90 0.80 0.10 asserted 0.99
s7 The proposed approach is first evaluated on synthetic data; posteriorly, the method is applied on real trajectories coming from moving pedestrians in an indoor environment. method 0.77 0.95 0.10 asserted 0.99

What kind of paper the classifier reports this is: method or tool 1.00 · evidence from observation or experiment 0.59.

What was examined, and what was not

sources read
  • arXiv listing abstract v1
not examined
  • full text
  • figures and tables
  • references and citing sentences
  • relations to other papers
levels run
  • P abstract
not run
  • S sections
  • T body sentences
  • C citations
  • R cross-paper relations

Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

This paper presents a methodology that aims at the incremental representation of areas inside environments in terms of attractive forces. It is proposed a parametric representation of velocity fields ruling the dynamics of moving agents. It is assumed that attractive spots in the environment are responsible for modifying the motion of agents. A switching model is used to describe near and far velocity fields, which in turn are used to learn attractive characteristics of environments. The effect of such areas is considered radial over all the scene. Based on the estimation of attractive areas, a map that describes their effects in terms of their localizations, ranges of action, and intensities is derived in an online way. Information of static attractive areas is added dynamically into a set of filters that describes possible interactions between moving agents and an environment. The proposed approach is first evaluated on synthetic data; posteriorly, the method is applied on real trajectories coming from moving pedestrians in an indoor environment.

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