PySensors is a Python package for sparse sensor placement
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Updated
Feb 17, 2026 - Python
PySensors is a Python package for sparse sensor placement
Software Suite for Sensor Placement and Informative Path Planning
Track 3: Sensor Placement
Simple Wireless-Sensor-Network Optimization using Genetic-Algorithm.
Spatial Interpolation in Python
A Matlab toolkit for sensor placement in water distribution systems
Comparing EnKF and WLS state estimators in power distribution networks equipped with smart meters and phasor measurement units
Informative Path Planning with Guaranteed Estimation Uncertainty (RSS 2026)
A Python package for tackling diverse environmental prediction tasks with NPs.
Desktop app for planning the camera and sensor rig of robot-learning setups: grasp visibility, depth validity, calibration, dataset audits and MuJoCo/LeRobot/Isaac exports. Linux, GPL-3.0.
Sensor Coverage Optimisation and Placement Engine detection model reference
3D LiDAR deployment optimization research code; source-available, no academic publication or commercial use without permission
Belief-state deep reinforcement learning for information-efficient autonomous beach microplastic sampling
Simultaneous sensor and actuator placement for contaminant detection
Sensor rig planner for autonomous-driving data collection: design, simulate in CARLA, calibrate, with an AI Copilot
Point process sensing library (sensepy)
Code for joint online parameter estimation and optimal sensor placement.
MPME sensor/frequency selection for subsurface radar imaging (IEEE TGRS 2023) - MATLAB
Reproducibility package for the paper "Machine Learning for Bus-Level Fault Location in Active Distribution Networks", including OpenDSS simulation, physics-informed PMU features, algorithmic sensor placement, and a reproducible 5-fold benchmark on the IEEE 123-bus feeder.
MWE (Minimal Working Example) of 2D Bayesian Optimisation over Antarctica
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