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Research report · Research Prototype

Uncertainty-Aware Navigation

Planning benchmark · Prototype · 2026–Present

This repository isolates the planning question: when a map is uncertain, does uncertainty-aware cost reduce unsafe navigation behavior compared with classical shortest-path planning?

GitHub repositoryResearch map

Abstract

Create a focused benchmark for comparing classical shortest-path planning with uncertainty-weighted navigation in controlled map scenarios.

Scientific question: Does uncertainty-weighted cost reduce unsafe navigation behavior compared with classical shortest-path planning?

Contribution: A small, controlled planning benchmark that isolates uncertainty cost from broader autonomy complexity.

Marked research artifact slot

Planning benchmark architecture

Architecture figure slot for verified diagrams of modules, data flow, and software boundaries.

Synthetic / planned visual

Marked research artifact slot

Grid map · uncertainty cost · planner comparison

Pipeline slot for GIFs or animations that explain estimation, planning, perception, or evaluation steps.

Synthetic / planned visual

Marked research artifact slot

Synthetic uncertainty-cost map

Demo slot reserved for real project videos or synthetic demos that are explicitly labeled as synthetic.

Synthetic / planned visual

Research questions

  • Can uncertainty-weighted planning reduce unsafe navigation behavior?
  • What path-length or computation-cost tradeoff appears when uncertainty is penalized?
  • Which safety metrics are most useful for controlled navigation experiments?

Methods

Grid-map simulationClassical planner baselinesUncertainty cost mapsSafety metric reporting

Implementation status

Implemented

  • Benchmark framing
  • Planner comparison plan
  • Metric list

Research prototype

  • Shortest path vs uncertainty-weighted planning
  • Risk-cost comparison

Planned

  • Executable benchmark
  • Plots
  • Connection to DynNav

Experiments and metrics

Experiments

  • Shortest path vs uncertainty-weighted planning
  • Collision-rate analysis
  • Accumulated risk-cost comparison

Metrics

  • path length
  • accumulated risk cost
  • collision rate — planned

Quantitative benchmark tables will be added only after reproducible experiments are available.

Limitations

  • Quantitative claims are intentionally withheld until reproducible benchmark runs are available.
  • Visual figures and GIFs are placeholders unless a project page explicitly states that an artifact is generated from real experiments.

Reproducibility plan

Experiment workflow

Each module is prepared to document configuration files, datasets, evaluation metrics, and repeated experiment runs before quantitative claims are shown.

Repository setup

Public repositories are linked when available. Private, planned, or incomplete repositories remain clearly labelled rather than being presented as finished systems.

Literature context

  • A* planning
  • Dijkstra
  • Navigation under uncertainty
  • Robotic path planning

Roadmap

  • Add executable first benchmark
  • Generate plots
  • Connect benchmark results to DynNav