← 研踪 PaperTrailarXiv:2611.03254 · v1
TRAILS: Trajectory Generation for Automated Indoor Locomotion Studies
首次提交 2026-11-02 23:00
版本更新 2026-11-02 23:00
雷达观测 2026-11-04 23:41
摘要
Virtual reality experiments involving navigation and simulated robot motion often require large, realistic environments and numerous distinct trajectories to avoid repetitive navigation while providing sufficient variation for controlled experiments. Designing such scenarios manually is labor-intensive, particularly when trajectories must satisfy predefined geometric and kinematic constraints while remaining diverse and comparable across experimental conditions. This paper presents TRAILS, an automated framework for generating complete virtual navigation scenarios consisting of an environment layout, a path, and a time-parameterized motion profile. The framework combines a constraint-based procedural environment generator inspired by Wave Function Collapse, trajectory generation using optimized cubic Bézier curves, and speed-profile generation subject to kinematic constraints. The generated scenarios provide diverse indoor environments with corridors, open spaces, and obstacles, together with trajectories of identical duration that vary in path geometry, wall proximity, and velocity profiles while minimizing systematic dependencies between these characteristics. The framework is designed as an easy-to-use tool requiring only a small number of intuitive user-defined parameters to automatically generate large sets of distinct navigation scenarios satisfying prescribed geometric and kinematic constraints. By relying on explicit, seed-controlled algorithmic procedures rather than data-driven models, the generated scenarios remain transparent, reproducible, and configurable, making the framework well suited for telepresence and human-subject experiments. The code is available at https://github.com/JucciK/Trails .
作者备注：8 pages, 4 figures, IEEE Telepresence 2026
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v1 · 2026-11-02 23:00 · 最新观测版本
TRAILS: Trajectory Generation for Automated Indoor Locomotion Studies
Virtual reality experiments involving navigation and simulated robot motion often require large, realistic environments and numerous distinct trajectories to avoid repetitive navigation while providing sufficient variation for controlled experiments. Designing such scenarios manually is labor-intensive, particularly when trajectories must satisfy predefined geometric and kinematic constraints while remaining diverse and comparable across experimental conditions. This paper presents TRAILS, an automated framework for generating complete virtual navigation scenarios consisting of an environment layout, a path, and a time-parameterized motion profile. The framework combines a constraint-based procedural environment generator inspired by Wave Function Collapse, trajectory generation using optimized cubic Bézier curves, and speed-profile generation subject to kinematic constraints. The generated scenarios provide diverse indoor environments with corridors, open spaces, and obstacles, together with trajectories of identical duration that vary in path geometry, wall proximity, and velocity profiles while minimizing systematic dependencies between these characteristics. The framework is designed as an easy-to-use tool requiring only a small number of intuitive user-defined parameters to automatically generate large sets of distinct navigation scenarios satisfying prescribed geometric and kinematic constraints. By relying on explicit, seed-controlled algorithmic procedures rather than data-driven models, the generated scenarios remain transparent, reproducible, and configurable, making the framework well suited for telepresence and human-subject experiments. The code is available at https://github.com/JucciK/Trails .
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