Evolutionary algorithms based multi objective trajectory planning of mobile robots

Abstract

This research work contributes in improving the existing algorithms for doing mobile robots trajectory planning and validating them in situations imitating real world environments. Stationary and moving obstacles were considered around the robot. Few simulations and 21 experiments were performed. Mobile robot trajectory planning for warehouse operations in green logistics was optimized. Results from various algorithms were compared and analyzed. A custom mobile robot was designed, fabricated and tested in various environments. Mobile robots applications are in all fields. Few applications of mobile robots in indoor situations are surveillance, cleaning, rescue and search operations, helping to old age people and handicapped people, cooking, entertaining people, etc. few applications of mobile robots in outdoor environments are logistics, transportation, security portals, etc. Autonomous mobile robots will navigate autonomously in both structured and unstructured environments. The structured environment is a known environment to the robot. It knows the position and behavior of all obstacles present inside a room. But in unstructured environment, these details are not known to the robot. It moves or works in an unknown environment. Messy and unpredictable situation with infinite and unforeseen disturbances viz., human intervention, temperature changes, moisture content changes, lighting intensity changes, climate changes, etc. Having motion in unstructured environment is a complex and difficult task. The robot has to continuously learn and practice to work by adopting the environmental changes and other disturbances newline