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Robust UKF Bearing-Only Target Tracking with Angle-Wrap and Outlier Traps

  • Task ID: robotics.ukf_bearing_only_tracking
  • Domain: robotics
  • Subdomain: state_estimation
  • Status: final
  • Benchmark set: seed42 (60 tasks)
  • Tags: ukf, bearing_only, target_tracking, angle_wrapping, sigma_points, state_estimation, outlier_rejection

Runtime and requirements

  • Estimated time: 45-90 minutes
  • Python: >=3.9
  • Packages: numpy>=1.24.0
  • GPU required: no
  • Network required: no

Public input and output contract

Inputs

  • bearing_obs.npy (data): Noisy bearing measurements [T] float64 (rad), one per filter step.
  • x0.npy (data): Initial state mean [4] float64: px, py, vx, vy.
  • P0.npy (data): Initial covariance [4, 4] float64 in the same layout.
  • task_info.json (data): Observer position, dt, state_layout, sequence length, and physical process/measurement noise scales.

Outputs

  • analysis.py (code): UKF bearing-only filter; reads data/ and writes state/covariance histories.
  • state_history.npy (data): Filtered state mean after each step, layout px, py, vx, vy.
  • covariance_history.npy (data): Filtered covariance after each step.
  • measurement_outlier_prob.npy (data): Probability/score in [0, 1] that each bearing measurement is a transient false return.

Public repository files

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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 f18382f03faf. Submission bundles, run logs, private scoring configuration, and private reference answers are not read by this page generator.