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Juan Andrade-Cetto

11 accepted papers

2022

Wolf: A Modular Estimation Framework for Robotics Based on Factor Graphs

RA-L 2022

This letter introduces <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Wolf</small> , a C++ estimation framework based on factor graphs and targeted at mobile robotics. <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/199

Cited by 18SourceScholar
2020

Multi-task closed-loop inverse kinematics stability through semidefinite programming

ICRA 2020poster

Today's complex robotic designs comprise in some cases a large number of degrees of freedom, enabling for multi-objective task resolution (e.g., humanoid robots or aerial manipulators). This paper tackles the local stability problem of a hierarchical closed-loop inverse kinematics algorithm for such…

Cited by 5SourceScholar
2019

Timed-Elastic Smooth Curve Optimization for Mobile-Base Motion Planning

IROS 2019poster

This paper proposes the use of piecewise Cn smooth curve for mobile-base motion planning and control, coined Timed-Elastic Smooth Curve (TESC) planner. Based on a Timed-Elastic Band, the problem is defined so that the trajectory lies on a spline in SE(2) with non-vanishing n-th derivatives at every…

Cited by 12SourceScholar
2018

Graph SLAM Sparsification With Populated Topologies Using Factor Descent Optimization

RA-L 2018

Current solutions to the simultaneous localization and mapping (SLAM) problem approach it as the optimization of a graph of geometric constraints. Scalability is achieved by reducing the size of the graph, usually in two phases. First, some selected nodes in the graph are marginalized and then, the

Cited by 31SourceScholar
2017

Trajectory Generation for Unmanned Aerial Manipulators Through Quadratic Programming

RA-L 2017

In this paper, a trajectory generation approach using quadratic programming is described for aerial manipulation, i.e., for the control of an aerial vehicle equipped with a robot arm. The proposed approach applies the online active set strategy to generate a feasible trajectory of the joints, in ord

Cited by 33SourceScholar
2017

Word Ordering and Document Adjacency for Large Loop Closure Detection in 2-D Laser Maps

RA-L 2017

We address in this letter the problem of loop closure detection for laser-based simultaneous localization and mapping (SLAM) of very large areas. Consistent with the state of the art, the map is encoded as a graph of poses, and to cope with very large mapping capabilities, loop closures are asserted

Cited by 14SourceScholar
2016

Hybrid Visual Servoing With Hierarchical Task Composition for Aerial Manipulation

RA-L 2016

In this letter, a hybrid visual servoing with a hierarchical task-composition control framework is described for aerial manipulation, i.e., for the control of an aerial vehicle endowed with a robot arm. The proposed approach suitably combines into a unique hybrid-control framework the main benefits

Cited by 136SourceScholar
2016

Observability analysis and optimal sensor placement in stereo radar odometry

ICRA 2016

Localization is the key perceptual process closing the loop of autonomous navigation, allowing self-driving vehicles to operate in a deliberate way. To ensure robust localization, autonomous vehicles have to implement redundant estimation processes, ideally independent in terms of the underlying phy

Cited by 9SourceScholar
2015

Active pose SLAM with RRT*

ICRA 2015poster

We propose a novel method for robotic exploration that evaluates paths that minimize both the joint path and map entropy per meter traveled. The method uses Pose SLAM to update the path estimate, and grows an RRT* tree to generate the set of candidate paths. This action selection mechanism contrasts…

Cited by 52SourceScholar
2015

High-frequency MAV state estimation using low-cost inertial and optical flow measurement units

IROS 2015poster

This paper develops a simple and low-cost method for 3D, high-rate vehicle state estimation, specially designed for free-flying Micro Aerial Vehicles (MAVs). We fuse observations from inertial measurement units and the recently appeared low-cost optical flow smart cameras. These smart cameras integr…

Cited by 37SourceScholar