DEVELOP, DESIGN, IMPLEMENT AND ANALYZE TWO NEW PATH FINDING ROBOTIC ALGORITHMS BASED ON SOFT SUBDIVISION SEARCH ALGORITHM

Abstract

Dangerous natural circumstances like highly explosive industries, space investigation exploration, radioactive chemical manufacturing plants, etc., are exceedingly hazardous for individuals to work with where autonomous mobile robots are the correct options. A mobile robot needs to choose the correct trajectory or complete an authentic movement, as the situation of the robot is not settled in space with the end goal to achieve the objective from its very own position. This paper based on different research concept for the proposed research.

Bipedal Locomotion is one of the most interesting control problems of current era, increasing demand of deploying them in hostile environments have given wings to the research in the field of legged locomotion. This Paper is focused on studying and modeling of point foot planar bipedal walkers as open link kinematic chains and to make a hardware model of acrobot walker and kneed walker able to walk passively down a slope. Simplified models of acrobot walker and kneed walker are developed and simple energy based linear controller is designed and implemented using partial feedback linearization. The controller developed helps to drive the bipedal in partially passive mode. The above chapter points out the local abilities of several path planners. Furthermore, human global vision can lead to a coherent partition of the path planning issue. We intend to manage simultaneously these local and global abilities by building an interaction between human and algorithms in order to have an efficient path planner [8] for a manikin or a robot with respect of ergonomic constraints or joints and mechanical limits of the robot.