TY  - JOUR
T1  - A constant-time SLAM back-end in the continuum between global mapping and submapping: application to visual stereo SLAM
A1  - Moreno, Francisco-Angel
A1  - Blanco, José-Luis
A1  - Gonzalez-Jimenez, Javier
JA  - International Journal of Robotics Research
Y1  - 2016
VL  - 35
IS  - 9
SP  - 1036
EP  - 1056
SN  - 0278-3649
UR  - http://mapir.uma.es/mapirwebsite/index.php/mapir-downloads/papers/228
M2  - doi: 10.1177/0278364915619238
N2  - This work addresses the development and application of a novel approach, called Sparser Relative Bundle Adjustment (SRBA), which exploits the inherent flexibility of the relative BA (RBA) framework to devise a continuum of strategies, ranging from RBA with linear graphs to classic BA in global coordinates, where submapping with local maps emerges as a natural intermediate solution. This method leads to graphs that can be optimized in bounded-time even at loop
closures, regardless of the loop length. Furthermore, it is shown that the pattern in which relative coordinate variables
are defined among keyframes has a significant impact on the graph optimization problem. By using the proposed
scheme, optimization can be done more efficiently than in standard RBA, allowing the optimization of larger local
maps for any given maximum computational cost. The main algorithms involved in the graph management, along
with their complexity analyses, are presented to prove their bounded-time nature. One key advance of the present
work is the demonstration that, under mild assumptions, the spanning trees for every single keyframe in the map
can be incrementally built by a constant-time algorithm, even for arbitrary graph topologies. We validate our proposal
within the scope of visual stereo SLAM by developing a complete system that includes a front-end that seamlessly
integrates several state-of-the-art computer vision techniques such as ORB features and bag-of-words, along with a
decision scheme for keyframe insertion and a SRBA-based back-end that operates as graph optimizer. Finally, a set of
experiments in both indoor and outdoor conditions is presented to test the capabilities of this approach. Open-source
implementations of the SRBA back-end and the stereo front-end have been released online.
M1  - img_url=http%3A%2F%2Fmapir.uma.es%2Ffamoreno%2Fimages%2Fpapers%2FIJRR_15_thumbnail.png
M1  - rank_indexname=JCR-2016
M1  - rank_pos_in_category=2
M1  - rank_num_in_category=26
M1  - rank_cat_name=ROBOTICS
M1  - impact_factor=5.301
ER  -