Robohub.org
 

Using geometry to help robots map their environment

by
26 February 2014



share this:

This post is part of our ongoing efforts to make the latest papers in robotics accessible to a general audience.

To get around unknown environments, most robots will need to build maps. To help them do so, robots can use the fact that human environments are often made of geometric shapes like circles, rectangles and lines. The latest paper in Autonomous Robots presents a flexible framework for geometrical robotic mapping in structured environments.

Most human designed environments, such as buildings, present regular geometrical properties that can be preserved in the maps that robots build and use. If some information about the general layout of the environment is available, it can be used to build more meaningful models and significantly improve the accuracy of the resulting maps. Human cognition exploits domain knowledge to a large extent, usually employing prior assumptions for the interpretation of situations and environments. When we see a wall, for example, we assume that it’s straight. We’ll probably also assume that it’s connected to another orthogonal wall.

This research presents a novel framework for the inference and incorporation of knowledge about the structure of the environment into the robotic mapping process. A hierarchical representation of geometrical elements (features) and relations between them (constraints) provides enhanced flexibility, also making it possible to correct wrong hypotheses. Various features and constraints are available, and it is very easy to add even more.

A variety of experiments with both synthetic and real data were conducted. The map below was generated from data measured by a robot navigating Killian Court at MIT using a laser scanner, and allows the geometrical properties of the environment to be well respected. You can easily tell that features are parallel, orthogonal and straight where needed.

map2

For more information, you can read the paper Feature based graph-SLAM in structured environments ( P. de la Puente and D. Rodriguez-Losada , Autonomous Robots – Springer US, Feb 2014) or ask questions below! 



tags: , ,


Autonomous Robots Blog Latest publications in the journal Autonomous Robots (Springer).
Autonomous Robots Blog Latest publications in the journal Autonomous Robots (Springer).





Related posts :



ep.

355

podcast

SLAM fused with Satellite Imagery (ICRA 2022), with John McConnell

John McConnell discusses the research presented at ICRA 2022 to reduce drift in SLAM algorithms by incorporating overhead satellite imagery.
25 May 2022, by

#ICRA2022, the great robotics scicommer – Day 1 video digest

Here I bring you some of the highlights in video of day 1 at the IEEE International Conference on Automation and Robotics (ICRA).
24 May 2022, by

Dan O’Mara: Turning Robotics Education on its Head | Sense Think Act Podcast #19

In this episode, Audrow Nash speaks to Dan O'Mara, who is the founder and COO of Circuit Launch and Mechlabs. Circuit Launch is a space for hardware entrepreneurs to work in Oakland, California, and M...

The IEEE International Conference on Robotics and Automation (ICRA) kicks off with the largest in-person participation and number of represented count

This is the first time the ICRA community is reunited after the pandemic, resulting in record breaking attendance with over 7,000 registrations and 95 countries represented.
ep.

354

podcast

Autonomous Flight Demo with CMU AirLab – ICRA Day 1, with Sebastian Scherer

Sebastian Scherer from CMU's Airlab gives us a behind-the-scenes demo at ICRA of their Autonomous Flight Control AI. Their approach aims to cooperate with human pilots and act the way they would. h...
24 May 2022, by
ep.

353

podcast

Robotics Grasping and Manipulation Competition Spotlight, with Yu Sun

Yu Sun, previous chair of the Robotics Grasping and Manipulation Competition, speaks on the value that this competition brought to the robotics community.
21 May 2022, by





©2021 - ROBOTS Association


 












©2021 - ROBOTS Association