Abstract
Path planning is intrinsically regarded as a multi-objective optimization problem (MOOP) that simultaneously optimizes the shortest path and the least collision-free distance to obstacles. This work develops a novel optimized approach using the genetic algorithm (GA) to drive the multi-objective evolutionary algorithm (MOEA) for the path planning of a mobile robot in a given finite environment. To represent the positions of a mobile robot as integer-type genes in a chromosome of the GA, a grid-based method is also introduced to relax the complex environment to a simple grid-based map. The system architecture is composed of a mobile robot, embedded with the robot operating system (ROS), the ArUco system and a laptop, executing the algorithms of path planning and image processing. Both simulations and experimental results are presented to verify the feasibility of the proposed method. In applications, this work can be employed in a commercial ball-collecting or an object-carrying robot.
Highlights
Over the past years, due to the advancement in the technologies of mechanics and electronics, mobile robots have been developed to cope with many challenging and hazardous tasks in a tough environment that is usually not considered a properly reachable workplace for humans
Each cell is sized in a square of 40 cm × 40 cm, and the entire experimental environment for the robot will be sized as 400 cm × 400 cm
The entire experimental procedure is divided into several single steps beginning from the start to the end positions of the mobile robot, as shown in Figs. 12a, 13a and 14a, which denote the results that the mobile robot is navigated to the destination with three, ten, and twenty obstacles, respectively
Summary
Due to the advancement in the technologies of mechanics and electronics, mobile robots have been developed to cope with many challenging and hazardous tasks in a tough environment that is usually not considered a properly reachable workplace for humans. There are extremely dangerous situations around the world, where bombs require to be defused to rescue people on site by soldiers or experts, whose lives are threatened owing to a number of unpredictable factors. For this reason, self-driven robots are very suitable to perform the extremely risky task, bomb removal, to keep the safety of soldiers or experts. The authorities of many countries around the world have issued the policies of a social distance which people maintain against infection and even of lockdown for people in the out-of-control areas to protect from the outbreak of coronavirus
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
