Maze Runner: Autonomous Maze Navigation with Line-Based Localization and Control Barrier Functions
Maze Runner: Autonomous Maze Navigation with Line-Based Localization and Control Barrier Functions
This research introduces Maze Runner, an open autonomy stack designed for autonomous navigation in mazes.
The study demonstrates end-to-end autonomous maze navigation in simulation using a ROS-free C++ stack that combines line-based localization with Control Barrier Functions for safety.
Source: arXiv Robotics — research abstracts · Read original article ↗
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What the source reports
Publisher-reported claims, with original evidence. These results have not been independently verified by RoboSignal.
- Environment
- SimulationOpen source S2
Reported numbers
route length
135
View original evidence
tive Controller (NMPC) tracks the plan while discrete-time Control Barrier Functions (CBFs) on world-frame LiDAR points keep the robot clear of walls and unmapped obstacles. The algorithms live in a ROS-free, unit-tested core library, and the whole stack builds and runs from a single reproducible environment. In simulation, the robot drives a 135 m route through the maze with 1.0 cm localization RMSE against the know
Open source S4localization RMSE
1
View original evidence
tive Controller (NMPC) tracks the plan while discrete-time Control Barrier Functions (CBFs) on world-frame LiDAR points keep the robot clear of walls and unmapped obstacles. The algorithms live in a ROS-free, unit-tested core library, and the whole stack builds and runs from a single reproducible environment. In simulation, the robot drives a 135 m route through the maze with 1.0 cm localization RMSE against the know
Open source S4
- paper: not_reported
- weights: not_reported
- dataset: not_reported
Source excerpts and review record
Automatically extracted; no manual editorial approval recorded.
arXiv:2611.12949v1 Announce Type: new Abstract: Maze navigation requires localization from sparse, repetitive geometry, planning through narrow corridors, and control that stays safe when the estimate or the map is wrong. We present Maze Runner, an open autonomy stack in C++ and ROS 2 that addresses these needs end to end on a simulated Husarion ROSbot XL with a 2D LiDAR in Gazebo. Perception extracts wall lines from
Open source S2
tive Controller (NMPC) tracks the plan while discrete-time Control Barrier Functions (CBFs) on world-frame LiDAR points keep the robot clear of walls and unmapped obstacles. The algorithms live in a ROS-free, unit-tested core library, and the whole stack builds and runs from a single reproducible environment. In simulation, the robot drives a 135 m route through the maze with 1.0 cm localization RMSE against the know
Open source S4
Source：arXiv Robotics — research abstracts · arxiv.org