A memetic evolutionary algorithm for real-time articulated kinematic motion

Solving kinematic motion is a challenging field of research which is relevant for various applications in character animation and robotics. This paper presents a novel and fast hybrid evolutionary algorithm for inverse kinematics which can handle fully constrained and highly articulated geometries with multiple end effectors and individual objectives. Several experiments on the 42 DoF human body mannequin and other kinematic models demonstrate a robust multimodal and multi-objective optimisation, and the ability to evolve accurate solutions in real-time while offering maximum flexibility for the design of custom cost functions.

[1]  Aaron Hertzmann,et al.  Style-based inverse kinematics , 2004, ACM Trans. Graph..

[2]  R. Storn,et al.  Differential Evolution - A simple and efficient adaptive scheme for global optimization over continuous spaces , 2004 .

[3]  Rainer Storn,et al.  Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..

[4]  Priyanka Ashok Shisode.  Computer animation , 2015 .

[5]  Andreas Aristidou,et al.  FABRIK: A fast, iterative solver for the Inverse Kinematics problem , 2011, Graph. Model..

[6]  Jianwei Zhang,et al.  An efficient hybridization of Genetic Algorithms and Particle Swarm Optimization for inverse kinematics , 2016, 2016 IEEE International Conference on Robotics and Biomimetics (ROBIO).

[7]  Claudio Melchiorri,et al.  Inverse Kinematics of Serial Manipulators in Cluttered Environments using a new Paradigm of Particle Swarm Optimization , 2014 .

[8]  S. Buss.  Introduction to Inverse Kinematics with Jacobian Transpose , Pseudoinverse and Damped Least Squares methods , 2004 .

[9]  Christopher Michael Clark,et al.  An adaptive niching genetic algorithm approach for generating multiple solutions of serial manipulator inverse kinematics with applications to modular robots , 2009, Robotica.

[10]  Wang Yaonan,et al.  Inverse Kinematics Solution for Robot Manipulator based on Neural Network under Joint Subspace , 2014 .

[11]  Patrick Beeson,et al.  TRAC-IK: An open-source library for improved solving of generic inverse kinematics , 2015, 2015 IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids).

[12]  B. Durmuş,et al.  An Inverse Kinematics Solution using Particle Swarm Optimization , 2022 .

[13]  Jürgen Leitner,et al.  Task-relevant roadmaps: A framework for humanoid motion planning , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[14]  Chih-Cheng Chen,et al.  A combined optimization method for solving the inverse kinematics problems of mechanical manipulators , 1991, IEEE Trans. Robotics Autom..

[15]  B. Biswal,et al.  A Neural Network Approach for Inverse Kinematic of a SCARA Manipulator , 2014 .

[16]  Wei-Min Shen,et al.  PASO : An Integrated , Scalable PSO-based Optimization Framework for Hyper-Redundant Manipulator Path Planning and Inverse Kinematics , 2014 .

[17]  Carla Elena González Uzcátegui.  A memetic approach to the inverse kinematics problem for robotic applications , 2014 .