Inference and Decision in Credal Occupancy Grids: Use Case on Trajectory Planning

SMAP: Simultaneous Mapping and Planning on Occupancy Grids

Occupancy grids are the most common framework when it comes to creating a map of the environment using a robot. This paper studies occupancy grids from the motion planning perspective and proposes a mapping method that provides richer data (map) for the purpose of planning and collision avoidance. Typically, in occupancy grid mapping, each cell contains a single number representing the probabil...

Trajectory Planning on Grids: Considering Speed Limit Constraints

Trajectory (path) planning is a well known and thoroughly studied field of automated planning. It is usually used in computer games, robotics or autonomous agent simulations. Grids are often used for regular discretization of continuous space. Many methods exist for trajectory (path) planning on grids, we address the well known A* algorithm and the state-of-the-art Theta* algorithm. Theta* algo...

Confidence-aware Occupancy Grids

Representation of Odometry Errors on Occupancy Grids

In this work we propose an enhanced model for mapping from sonar sensors and odometry that allows a robot to represent an environment map in a more suitable way to both the sonar sensory data and odometry system of the robot. We use a stochastic modelling of the errors that brings up reliable information. As a contribution, we obtain a final map that is more coherent with the reality of the ori...

2D Semantic Mapping on Occupancy Grids

In recent years, techniques for building metric maps of indoor environments have been intensely studied, and they perform very well in noumerous applications. Simultaneous Localization and Mapping (SLAM) methods produce globally consistent, metric maps of the explored environment. Although such maps describe how the environment looks like and can be used for navigation, there exist no abstracte...