Unsupervised calibration of wheeled mobile platforms

Cicco, Maurilio Di; Corte, Bartolomeo Della; Grisetti, Giorgio

doi:10.1109/icra.2016.7487631

Cited by 9 publications

(11 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In calibration, ILS has been used extensively since the first works appeared until these days [18][19][20]. Common works in batch calibration involve relatively small state spaces covering only the parameters to be estimated.…”

Section: Ils In Roboticsmentioning

confidence: 99%

See 1 more Smart Citation

Least Squares Optimization: From Theory to Practice

et al. 2020

Self Cite

View full text Add to dashboard Cite

Nowadays, Nonlinear Least-Squares embodies the foundation of many Robotics and Computer Vision systems. The research community deeply investigated this topic in the last few years, and this resulted in the development of several open-source solvers to approach constantly increasing classes of problems. In this work, we propose a unified methodology to design and develop efficient Least-Squares Optimization algorithms, focusing on the structures and patterns of each specific domain. Furthermore, we present a novel open-source optimization system that addresses problems transparently with a different structure and designed to be easy to extend. The system is written in modern C++ and runs efficiently on embedded systemsWe validated our approach by conducting comparative experiments on several problems using standard datasets. The results show that our system achieves state-of-the-art performances in all tested scenarios.

show abstract

Section: Ils In Roboticsmentioning

confidence: 99%

“…The previous formulation of GN algorithm uses vector addition and subtraction to compute the error e k in Equation ( 17) and to apply the increments in Equation (20). However, these two operations are only defined in Euclidean spaces.…”

Section: Non-euclidean Spacesmentioning

confidence: 99%

Least Squares Optimization: From Theory to Practice

et al. 2020

Self Cite

View full text Add to dashboard Cite

show abstract

“…Recently, Cicco et al [7] proposed an unsupervised calibration procedure. By exploring and recording the effects of elementary motions on the uncertainty of the parameters estimate, their method chooses autonomously at every time the best next motion for the robot to perform to further reduce the uncertainty.…”

Section: A Related Workmentioning

confidence: 99%

“…where J ∆ ik ∆ij , J ∆ ik δ k , J δ k b k and J b k c are respectively the Jacobian blocks of (9), (8) and (6)(7).…”

Section: Delta Jacobian Pre-integrationmentioning

confidence: 99%

See 1 more Smart Citation

Joint on-manifold self-calibration of odometry model and sensor extrinsics using pre-integration

Deray

Solà

Andrade‐Cetto

2019

2019 European Conference on Mobile Robots (ECMR)

View full text Add to dashboard Cite

This paper describes a self-calibration procedure that jointly estimates the extrinsic parameters of an exteroceptive sensor able to observe ego-motion, and the intrinsic parameters of an odometry motion model, consisting of wheel radii and wheel separation. We use iterative nonlinear onmanifold optimization with a graphical representation of the state, and resort to an adaptation of the pre-integration theory, initially developed for the IMU motion sensor, to be applied to the differential drive motion model. For this, we describe the construction of a pre-integrated factor for the differential drive motion model, which includes the motion increment, its covariance, and a first-order approximation of its dependence with the calibration parameters. As the calibration parameters change at each solver iteration, this allows a posteriori factor correction without the need of re-integrating the motion data. We validate our proposal in simulations and on a real robot and show the convergence of the calibration towards the true values of the parameters. It is then tested online in simulation and is shown to accommodate to variations in the calibration parameters when the vehicle is subject to physical changes such as loading and unloading a freight.

show abstract