DR. GUSTAVO ARECHAVALETA

@conference{conf:Delfin2016,

title = {Humanoid Localization and Navigation using a Visual Memory},

author = {Delfin, Josafat and Becerra, H\'{e}ctor M and Arechavaleta, Gustavo },

doi = {10.1109/HUMANOIDS.2016.7803354},

issn = {2164-0580},

year  = {2016},

date = {2016-11-15},

booktitle = {IEEE-RAS 16th International Conference on Humanoid Robots},

pages = {725-731},

publisher = {IEEE},

abstract = {A visual memory (VM) is a topological map in which a set of key images organized in form of a graph represents an environment. In this paper, a navigation strategy for humanoid robots addressing the problems of localization, visual path planning and path following based on a VM is proposed. Assuming that the VM is given, the main contributions of the paper are: 1) A novel pure vision-based localization method. 2) The introduction of the estimated rotation between key images in the path planning stage to benefit paths with enough visual information and with less effort of robot rotation. 3) The integration of the complete navigation strategy and its experimental evaluation with a Nao robot in an unstructured environment. The humanoid robot is modeled as a holonomic system and the strategy might be used in different scenarios like corridors, uncluttered or cluttered environments.},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{7041439,

title = {3D shape reconstruction from a humanoid generated video sequence},

author = {Martinez-Gonzalez, Pablo and Varas, David and Castelan, Mario and Camacho, Margarita and Marques, Ferran and Arechavaleta, Gustavo },

url = {http://ieeexplore.ieee.org/document/7041439/?arnumber=7041439\&tag=1},

doi = {10.1109/HUMANOIDS.2014.7041439},

issn = {2164-0572},

year  = {2014},

date = {2014-11-01},

booktitle = {2014 IEEE-RAS International Conference on Humanoid Robots},

pages = {699-706},

abstract = {This paper presents a strategy for estimating the geometry of an interest object from a monocular video sequence acquired by a walking humanoid robot. The problem is solved using a space carving algorithm, which relies on both the accurate extraction of the occluding boundaries of the object as well as the precise estimation of the camera pose for each video frame. For data acquisition, a monocular visual-based control has been developed that drives the trajectory of the robot around an object placed on a small table. Due to the stepping of the humanoid, the recorded sequence is contaminated with artefacts that affect the correct extraction of contours along the video frames. To overcome this issue, a method that assigns a fitness score for each frame is proposed, delivering a subset of camera poses and video frames that produce consistent 3D shape estimations of the objects used for experimental evaluation.},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{6651548,

title = {An active strategy for the simultaneous localization and reconstruction of a 3D object from a humanoid platform},

author = {Delfin, Josafat and Mar, Oscar and Hayet, Jean Bernard and Castelan, Mario and Arechavaleta, Gustavo },

url = {http://ieeexplore.ieee.org/document/6651548/?arnumber=6651548},

doi = {10.1109/HUMANOIDS.2012.6651548},

issn = {2164-0572},

year  = {2012},

date = {2012-11-01},

booktitle = {2012 12th IEEE-RAS International Conference on Humanoid Robots (Humanoids 2012)},

pages = {384-389},

abstract = {This paper proposes a novel approach for the simultaneous localization and reconstruction of a 3D object. This reconstruction is done with a small humanoid platform by the only means of monocular vision.We combine (1) a stochastic control approach to decide how to move the robot such that the object can be both localized with respect to the robot and correctly reconstructed, and (2) a space carving approach for the 3D reconstruction of the object that merges the acquired monocular views into a coherent model. We present a set of very promising results obtained with a NAO platform.},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{5686313,

title = {Multilinear decomposition of human walking paths},

author = {Ramirez-Bejarano, Christian and Castelan, Mario and Arechavaleta, Gustavo },

url = {http://ieeexplore.ieee.org/document/5686313/?arnumber=5686313},

doi = {10.1109/ICHR.2010.5686313},

issn = {2164-0572},

year  = {2010},

date = {2010-12-01},

booktitle = {2010 10th IEEE-RAS International Conference on Humanoid Robots},

pages = {492-497},

abstract = {In a previous work, the authors have shown how the Principal Components Analysis (PCA) of a set of human walking paths provides sufficient information to derive a linear human-like path generator based on examples. The present work aims to provide an analysis of human walking paths from the perspective of multilinear algebra, using the n-mode Singular Value Decomposition (SVD). This decomposition subsumes the conventional PCA and extends its capabilities to study the interaction between the different vector spaces attached to the data. The training set consists of sixty routes performed three times by five different subjects for a total of 900 examples. The outcome of this decomposition is a novel multilinear model capable of revealing the global shape variations between the different vector spaces, particularly, exhibiting the planning strategies that each subject seemed to use to approach to the different targets. In addition, we sketch how the multilinear model may be used to synthesize new routes for the hypothetical case of a subject trying to reach a moving target.},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{5379595,

title = {Approximating the reachable space of human walking paths: a low dimensional linear approach},

author = {Castelan, Mario and Arechavaleta, Gustavo },

url = {http://ieeexplore.ieee.org/document/5379595/?arnumber=5379595},

doi = {10.1109/ICHR.2009.5379595},

issn = {2164-0572},

year  = {2009},

date = {2009-12-01},

booktitle = {2009 9th IEEE-RAS International Conference on Humanoid Robots},

pages = {81-86},

abstract = {In this work, we aim to exhibit the geometrical shape primitives of human walking trajectories using a statistical model constructed through Principal Component Analysis. This analysis provides sufficient information to derive a linear human-like path generator based on examples. The examples are provided by a motion capture database of human walking trajectories. The proposed model captures the shape of trajectories in terms of path length and deformation. We have successfully applied our model to compute a good approximation of the reachable space of human walking. This can be done with a negligible computational cost since it is based on a linear combination of basis human paths.},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}