MuNES: Multifloor Navigation Including Elevators and Stairs

TL;DR

MuNES tackles autonomous multifloor navigation by constructing a single consistent map that includes elevators and stairs. It integrates barometric pressure-based elevation estimation with floor-labeled loop closure and a voxelized representation, enabling efficient A*-based trajectory planning that accounts for elevator waiting times. The approach demonstrates accurate elevation estimation, robust loop closure, and realistic interfloor trajectories on campus data, highlighting practical applicability for mobile robots. The authors provide code and data to support reproducibility.

Abstract

We propose a scheme called MuNES for single mapping and trajectory planning including elevators and stairs. Optimized multifloor trajectories are important for optimal interfloor movements of robots. However, given two or more options of moving between floors, it is difficult to select the best trajectory because there are no suitable indoor multifloor maps in the existing methods. To solve this problem, MuNES creates a single multifloor map including elevators and stairs by estimating altitude changes based on pressure data. In addition, the proposed method performs floor-based loop detection for faster and more accurate loop closure. The single multifloor map is then voxelized leaving only the parts needed for trajectory planning. An optimal and realistic multifloor trajectory is generated by exploring the voxels using an A* algorithm based on the proposed cost function, which affects realistic factors. We tested this algorithm using data acquired from around a campus and note that a single accurate multifloor map could be created. Furthermore, optimal and realistic multifloor trajectory could be found by selecting the means of motion between floors between elevators and stairs according to factors such as the starting point, ending point, and elevator waiting time. The code and data used in this work are available at https://github.com/donghwijung/MuNES.

Figures (6)

• Figure 1: Result of multidestination trajectory planning including intermediate destinations. The purple and blue colors indicate trajectory between destinations and returning trajectory to the starting point, respectively. The other colors from red to dark purple represent the starting, ending, and intermediate pints. The order of points for the trajectory is red, yellow, green, blue, and dark purple.
• Figure 2: Process of MuNES; the point cloud map (left) is voxelized and represented as a voxel map (middle); MuNES uses this voxel map to proceed with multifloor trajectory planning (right).
• Figure 3: System architecture of the mapping part in MuNES.
• Figure 4: Pressure change from the third to the second floor in building $1$.
• Figure 5: \ref{['fig:loam']},\ref{['fig:loam2']} Results of multifloor mapping using LOAM and \ref{['fig:mufe']}, \ref{['fig:mufe2']} the proposed method; \ref{['fig:loam']}, \ref{['fig:mufe']} denote the results of mapping with an elevator (red) and stairs (blue), and \ref{['fig:loam2']}, \ref{['fig:mufe2']} represent the results of mapping with elevators on both sides (red).