An adaptive truncation criterion, for linesearch-based truncated Newton methods in large scale nonconvex optimization

Caliciotti, Andrea; Fasano, Giovanni; Nash, Stephen G.; Roma, Massimo

doi:10.1016/j.orl.2017.10.014

Cited by 17 publications

(23 citation statements)

References 30 publications

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“…The future work will mainly focus on the following aspects. First of all, we will introduce the heuristic adaptive truncation criterion [27] into the NICCD method to improve the convergence rate. Next, we will improve the NICCD method to become a more effective method with respect to avoiding a singularity location and local minimum, which, in turn, will enhance the accuracy and robustness of the method.…”

Section: Discussionmentioning

confidence: 99%

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A General Approach Based on Newton’s Method and Cyclic Coordinate Descent Method for Solving the Inverse Kinematics

et al. 2019

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The inverse kinematics of robot manipulators is a crucial problem with respect to automatically controlling robots. In this work, a Newton-improved cyclic coordinate descent (NICCD) method is proposed, which is suitable for robots with revolute or prismatic joints with degrees of freedom of any arbitrary number. Firstly, the inverse kinematics problem is transformed into the objective function optimization problem, which is based on the least-squares form of the angle error and the position error expressed by the product-of-exponentials formula. Thereafter, the optimization problem is solved by combining Newton’s method with the improved cyclic coordinate descent (ICCD) method. The difference between the proposed ICCD method and the traditional cyclic coordinate descent method is that consecutive prismatic joints and consecutive parallel revolute joints are treated as a whole in the former for the purposes of optimization. The ICCD algorithm has a convenient iterative formula for these two cases. In order to illustrate the performance of the NICCD method, its simulation results are compared with the well-known Newton–Raphson method using six different robot manipulators. The results suggest that, overall, the NICCD method is effective, accurate, robust, and generalizable. Moreover, it has advantages for the inverse kinematics calculations of continuous trajectories.

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Section: Discussionmentioning

confidence: 99%

“…In particular, some scholars have improved the truncation criterion of Newton's method, which avoids "over-solving" of the Newton equation as much as possible. The representative method is the heuristic adaptive truncation criterion proposed by [27,28].…”

Section: Newton's Methodsmentioning

confidence: 99%

A General Approach Based on Newton’s Method and Cyclic Coordinate Descent Method for Solving the Inverse Kinematics

et al. 2019

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“…Specification refers to a system with a static structure and invariable behaviour, or a system with a variable structure at a certain time instant that both can be efficiently solved by using advanced optimization techniques proposed in [52,53]. To specify a particular system, instances of the relevant concepts appearing in the general system model should be concretised.…”

Section: Specification Of a Particular Robot Control Systemmentioning

confidence: 99%

EARL—Embodied Agent-Based Robot Control Systems Modelling Language

et al. 2020

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The paper presents the Embodied Agent-based Robot control system modelling Language (EARL). EARL follows a Model-Driven Software Development approach (MDSD), which facilitates robot control system development. It is based on a mathematical method of robot controller specification, employing the concept of an Embodied Agent, and a graphical modelling language: System Modelling Language (SysML). It combines the ease of use of SysML with the precision of mathematical specification of certain aspects of the designed system. It makes the whole system specification effective, from the point of view of the time needed to create it, conciseness of the specification and the possibility of its analysis. By using EARL it is possible to specify systems both with fixed and variable structure. This was achieved by introducing a generalised system model and presenting particular structures of the system in terms of modelling block configurations adapted by using instances. FABRIC framework was created to support the implementation of EARL-based controllers. EARL is compatible with component based robotic middlewares (e.g., ROS and Orocos).

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“…Data from different experimental settings are reported, along with performance profiles, which highlight the advantages of adopting the proposal in [1] . The use of the performance profiles [3] is typically advised in the community of Nonlinear Optimization, since they clearly summarize in one plot the comparison among several codes over an entire test set.…”

Section: Datamentioning

confidence: 99%

Data and performance profiles applying an adaptive truncation criterion, within linesearch-based truncated Newton methods, in large scale nonconvex optimization

et al. 2018

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In this paper, we report data and experiments related to the research article entitled “An adaptive truncation criterion, for linesearch-based truncated Newton methods in large scale nonconvex optimization” by Caliciotti et al. [1]. In particular, in Caliciotti et al. [1], large scale unconstrained optimization problems are considered by applying linesearch-based truncated Newton methods. In this framework, a key point is the reduction of the number of inner iterations needed, at each outer iteration, to approximately solving the Newton equation. A novel adaptive truncation criterion is introduced in Caliciotti et al. [1] to this aim. Here, we report the details concerning numerical experiences over a commonly used test set, namely CUTEst (Gould et al., 2015) [2]. Moreover, comparisons are reported in terms of performance profiles (Dolan and Moré, 2002) [3], adopting different parameters settings. Finally, our linesearch-based scheme is compared with a renowned trust region method, namely TRON (Lin and Moré, 1999) [4].

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An adaptive truncation criterion, for linesearch-based truncated Newton methods in large scale nonconvex optimization

Cited by 17 publications

References 30 publications

A General Approach Based on Newton’s Method and Cyclic Coordinate Descent Method for Solving the Inverse Kinematics

A General Approach Based on Newton’s Method and Cyclic Coordinate Descent Method for Solving the Inverse Kinematics

EARL—Embodied Agent-Based Robot Control Systems Modelling Language

Data and performance profiles applying an adaptive truncation criterion, within linesearch-based truncated Newton methods, in large scale nonconvex optimization

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