Dynamic Motion Planning Algorithm for a Biped Robot Using Fast Marching Method Hybridized with Regression Search

Abstract

In the past few years, studies of biped robot locomotion and navigation have increased enormously due to its ease in mobility in the terrains that are designed exclusively for the humans. To navigate the biped robot in static and dynamic environments without hitting obstacles is a challenging task. In the present research, the authors have developed a hybridized motion planning algorithm that is, fast marching method hybridized with regression search (FMMHRS) methodology. In this work, initially the fast marching algorithm has been used to observe the environment and identify the path from start to final goal. Later on, the regression search method is combined with the fast marching method (FMM) algorithm to optimize the path without hitting any obstacles. The main objective of the present research work is to generate the path for both the static and dynamic scenarios in simulation and in a real environment. To conduct the testing of the proposed algorithm, the authors have chosen an 18-DOF two legged robot that was developed in our laboratory.

Cognitive robotics software development aspects based on experiments of future software engineers

“…At the SCSS2019 workshop, which is organized annually by the Automation and Information Technology department at the ICDT Research and Development Institute of UTBV, Romania, 45 papers were presented, of which 16 in the field of robotics. In the three sections: Automation [1], Information Technology [2] and Robotics [3][4] [5], the main topics presented were mobile robots with traffic sign recognition, object tracking [6], path planning [7], gesture recognition, voice command processing [8], motion planning [9], 3D object reconstruction, parallel robot investigations [10] and others.…”