Robohub.org
 

Vision-based navigation with motion blur

by
20 July 2010



share this:

Robots often need to know where they are in the world to navigate efficiently. One of the cheapest ways to localize is to strap a camera on-board and extract visual features from the environment. However, challenges arise when robots move fast enough to create motion blur. The problem is that blurry images lead to decreased accuracy in localization. Because of this, robots that move too fast might no longer be able to localize and as a result might get lost or need to stop and re-localize.

Instead, Hornung et al. propose to use reinforcement learning to determine the optimal policy which allows the robots to go at speeds appropriate for navigation while ensuring that they get to destination as fast as possible. The actual implementation uses an augmented Markov decision process (MDP) to model the navigation task.

The learned policy is then compressed using a clustering technique to avoid being memory-sassy, which would be a major limitation for robots with low storage capacity.

Experiments were successfully conducted on two different robots in indoor and outdoor scenarios (see video) and the robots were faster than if they had navigated at constant speed. In the future, Hornung et al. hope to implement their system on fast moving robots, such as unmanned aerial vehicles!



tags:


Sabine Hauert is President of Robohub and Associate Professor at the Bristol Robotics Laboratory
Sabine Hauert is President of Robohub and Associate Professor at the Bristol Robotics Laboratory





Related posts :



Open Robotics Launches the Open Source Robotics Alliance

The Open Source Robotics Foundation (OSRF) is pleased to announce the creation of the Open Source Robotics Alliance (OSRA), a new initiative to strengthen the governance of our open-source robotics so...

Robot Talk Episode 77 – Patricia Shaw

In the latest episode of the Robot Talk podcast, Claire chatted to Patricia Shaw from Aberystwyth University all about home assistance robots, and robot learning and development.
18 March 2024, by

Robot Talk Episode 64 – Rav Chunilal

In the latest episode of the Robot Talk podcast, Claire chatted to Rav Chunilal from Sellafield all about robotics and AI for nuclear decommissioning.
31 December 2023, by

AI holidays 2023

Thanks to those that sent and suggested AI and robotics-themed holiday videos, images, and stories. Here’s a sample to get you into the spirit this season....
31 December 2023, by and

Faced with dwindling bee colonies, scientists are arming queens with robots and smart hives

By Farshad Arvin, Martin Stefanec, and Tomas Krajnik Be it the news or the dwindling number of creatures hitting your windscreens, it will not have evaded you that the insect world in bad shape. ...
31 December 2023, by

Robot Talk Episode 63 – Ayse Kucukyilmaz

In the latest episode of the Robot Talk podcast, Claire chatted to Ayse Kucukyilmaz from the University of Nottingham about collaboration, conflict and failure in human-robot interactions.
31 December 2023, by





Robohub is supported by:




Would you like to learn how to tell impactful stories about your robot or AI system?


scicomm
training the next generation of science communicators in robotics & AI


©2024 - Association for the Understanding of Artificial Intelligence


 












©2021 - ROBOTS Association