Trajectory optimization in both static and dynamic environments

This paper proposes a new approach to optimize the path of a mobile traveling through environments containing both static and dynamic obstacles. It aims to accurately represent the known environment in order to give the mobile robot all the required information needed to move through the plan without striking any obstacles. When the workspace modeling is too complex, the algorithm will more likely need too much time to treat the modeling data (data used to model the environment in the program) and consequently slow the execution of the robot's tasks. The particularity of the method is in the representation of the static environment in a judicious way facilitating the path planning and reducing the processing time. Moreover, when an unexpected obstacle blocks the robot trajectory, the method uses the robot sensors to detect the obstacle, finds a best way to circumvent it and then resumes its path toward the desired destination. Experimental results showed the effectiveness of the proposed approach.