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Particle Filter with Weight Degeneracy and Angle Wrapping¶

Task ID: robotics.particle_filter
Domain: robotics
Subdomain: state_estimation
Status: final
Benchmark set: seed42 (60 tasks)
Tags: particle_filter, sequential_monte_carlo, range_bearing, angle_wrapping, log_weights, weight_degeneracy, ess, resampling, nees

Runtime and requirements¶

Estimated time: 60-120 minutes
Python: >=3.10
Packages: numpy>=1.24, scipy>=1.10, pandas>=2.0, matplotlib>=3.7
GPU required: no
Network required: no

Public input and output contract¶

Inputs¶

data/measurements.npz (data): A deterministic target-tracking dataset with nonlinear two-channel measurements, timing, and observation masks.

Outputs¶

analysis.py (code): Agent-authored particle-filter analysis script.
results/state_estimates.csv (data): Per-time estimated state mean and covariance diagonal.
results/filter_diagnostics.csv (data): Per-time RMSE, NEES, ESS, log-weight range, and resampling diagnostics.
results/summary.json (data): Scalar summary of RMSE, NEES, ESS, resampling, degeneracy, and angle wrapping behavior.
results/overview.png (figure): Diagnostic plot of trajectory, errors, ESS, and measurement observations.
results/conclusion.txt (conclusion): Short scientific conclusion about filter stability and any detected numerical pathologies.

Public repository files¶

View this task in ASI-Bench

Formal benchmark task directories in the public repository are metadata-only. Versioned prompts and inputs are distributed through the pinned benchmark dataset.

task_meta.yaml

Provenance¶

This task is included in the current seed42 benchmark set at dataset revision f11a199f71fb4b854ac43a1bf548d5df519141a9.

This page is generated only from files tracked in the public ASI-Bench repository at commit c9c1ba960854. Submission bundles, run logs, private scoring configuration, and private reference answers are not read by this page generator.