Segmatch: Segment based place recognition in 3d point clouds
Place recognition in 3D data is a challenging task that has been commonly approached by
adapting image-based solutions. Methods based on local features suffer from ambiguity and …
adapting image-based solutions. Methods based on local features suffer from ambiguity and …
Planning in the continuous domain: A generalized belief space approach for autonomous navigation in unknown environments
We investigate the problem of planning under uncertainty, with application to mobile
robotics. We propose a probabilistic framework in which the robot bases its decisions on the …
robotics. We propose a probabilistic framework in which the robot bases its decisions on the …
Scaling up gaussian belief space planning through covariance-free trajectory optimization and automatic differentiation
Belief space planning provides a principled framework to compute motion plans that
explicitly gather information from sensing, as necessary, to reduce uncertainty about the …
explicitly gather information from sensing, as necessary, to reduce uncertainty about the …
The complex-step derivative approximation on matrix lie groups
The complex-step derivative approximation is a numerical differentiation technique that can
achieve analytical accuracy, to machine precision, with a single function evaluation. In this …
achieve analytical accuracy, to machine precision, with a single function evaluation. In this …
Automatic differentiation for Riemannian optimization on low-rank matrix and tensor-train manifolds
In scientific computing and machine learning applications, matrices and more general
multidimensional arrays (tensors) can often be approximated with the help of low-rank …
multidimensional arrays (tensors) can often be approximated with the help of low-rank …
Automatic multivector differentiation and optimization
In this work, we present a novel approach to nonlinear optimization of multivectors in the
Euclidean and conformal model of geometric algebra by introducing automatic …
Euclidean and conformal model of geometric algebra by introducing automatic …
Automatic differentiation of uncertainties: an interval computational differentiation for first and higher derivatives with implementation
H Dawood, N Megahed - PeerJ Computer Science, 2023 - peerj.com
Acquiring reliable knowledge amidst uncertainty is a topical issue of modern science.
Interval mathematics has proved to be of central importance in co** with uncertainty and …
Interval mathematics has proved to be of central importance in co** with uncertainty and …
Motor estimation using heterogeneous sets of objects in conformal geometric algebra
In this paper we present a novel method for nonlinear rigid body motion estimation from
noisy data using heterogeneous sets of objects of the conformal model in geometric algebra …
noisy data using heterogeneous sets of objects of the conformal model in geometric algebra …
Manifold geometry with fast automatic derivatives and coordinate frame semantics checking in C++
Computer vision and robotics problems often require representation and estimation of poses
on the SE (3) manifold. Developers of algorithms that must run in real time face several time …
on the SE (3) manifold. Developers of algorithms that must run in real time face several time …
A Consistent and Categorical Axiomatization of Differentiation ArithmeticApplicable to First and Higher Order Derivatives
H Dawood - Punjab University Journal of Mathematics, 2020 - journals.pu.edu.pk
Differentiation arithmetic is a principal and accurate techniquefor the computational
evaluation of derivatives of first and higher order. This article aims at recasting real …
evaluation of derivatives of first and higher order. This article aims at recasting real …