TY - GEN
T1 - Using sketch-maps for robot navigation
T2 - 14th International Symposium on Safety, Security and Rescue Robotics, SSRR 2016
AU - Mielle, Malcolm
AU - Magnusson, Martin
AU - Lilienthal, Achim J.
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/12/14
Y1 - 2016/12/14
N2 - We present a study on sketch-map interpretation and sketch to robot map matching, where maps have nonuniform scale, different shapes or can be incomplete. For humans, sketch-maps are an intuitive way to communicate navigation information, which makes it interesting to use sketch-maps for human robot interaction; e.g., in emergency scenarios. To interpret the sketch-map, we propose to use a Voronoi diagram that is obtained from the distance image on which a thinning parameter is used to remove spurious branches. The diagram is extracted as a graph and an efficient error-tolerant graph matching algorithm is used to find correspondences, while keeping time and memory complexity low. A comparison against common algorithms for graph extraction shows that our method leads to twice as many good matches. For simple maps, our method gives 95% good matches even for heavily distorted sketches, and for a more complex real-world map, up to 58%. This paper is a first step toward using unconstrained sketch-maps in robot navigation.
AB - We present a study on sketch-map interpretation and sketch to robot map matching, where maps have nonuniform scale, different shapes or can be incomplete. For humans, sketch-maps are an intuitive way to communicate navigation information, which makes it interesting to use sketch-maps for human robot interaction; e.g., in emergency scenarios. To interpret the sketch-map, we propose to use a Voronoi diagram that is obtained from the distance image on which a thinning parameter is used to remove spurious branches. The diagram is extracted as a graph and an efficient error-tolerant graph matching algorithm is used to find correspondences, while keeping time and memory complexity low. A comparison against common algorithms for graph extraction shows that our method leads to twice as many good matches. For simple maps, our method gives 95% good matches even for heavily distorted sketches, and for a more complex real-world map, up to 58%. This paper is a first step toward using unconstrained sketch-maps in robot navigation.
UR - http://www.scopus.com/inward/record.url?scp=85009754966&partnerID=8YFLogxK
U2 - 10.1109/SSRR.2016.7784307
DO - 10.1109/SSRR.2016.7784307
M3 - Conference contribution
AN - SCOPUS:85009754966
T3 - SSRR 2016 - International Symposium on Safety, Security and Rescue Robotics
SP - 252
EP - 257
BT - SSRR 2016 - International Symposium on Safety, Security and Rescue Robotics
A2 - Melo, Kamilo
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 23 October 2016 through 27 October 2016
ER -