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Multi-legged robot dynamics navigation model with optical flow

Edgar A. Martínez-García (Laboratorio de Robótica, Universidad Autonoma de Ciudad Juarez, Juarez, Mexico)
Luz Abril Torres-Méndez (Robótica y Manufactura Avanzada, CINVESTAV Campus Saltillo, Ramos Arizpe, Mexico)
Mohan Rajesh Elara (Product Development Pillar, Singapore University of Technology and Design, Singapore)

International Journal of Intelligent Unmanned Systems

ISSN: 2049-6427

Article publication date: 6 May 2014




The purpose of this paper is to establish analytical and numerical solutions of a navigational law to estimate displacements of hyper-static multi-legged mobile robots, which combines: monocular vision (optical flow of regional invariants) and legs dynamics.


In this study the authors propose a Euler-Lagrange equation that control legs’ joints to control robot's displacements. Robot's rotation and translational velocities are feedback by motion features of visual invariant descriptors. A general analytical solution of a derivative navigation law is proposed for hyper-static robots. The feedback is formulated with the local speed rate obtained from optical flow of visual regional invariants. The proposed formulation includes a data association algorithm aimed to correlate visual invariant descriptors detected in sequential images through monocular vision. The navigation law is constrained by a set of three kinematic equilibrium conditions for navigational scenarios: constant acceleration, constant velocity, and instantaneous acceleration.


The proposed data association method concerns local motions of multiple invariants (enhanced MSER) by minimizing the norm of multidimensional optical flow feature vectors. Kinematic measurements are used as observable arguments in the general dynamic control equation; while the legs joints dynamics model is used to formulate the controllable arguments.


The given analysis does not combine sensor data of any kind, but only monocular passive vision. The approach automatically detects environmental invariant descriptors with an enhanced version of the MSER method. Only optical flow vectors and robot's multi-leg dynamics are used to formulate descriptive rotational and translational motions for self-positioning.



The authors would like to thank PROMEP for research grants to academic body UACJ-CA-75.


A. Martínez-García, E., Abril Torres-Méndez, L. and Rajesh Elara, M. (2014), "Multi-legged robot dynamics navigation model with optical flow", International Journal of Intelligent Unmanned Systems, Vol. 2 No. 2, pp. 121-139.



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