  If we give a robot the task of moving an object from its current position to
another location in an unknown environment, the robot must explore the map,
identify all types of obstacles, and then determine the best route to complete
the task. We proposed a mathematical model to find an optimal path planning
that avoids collisions with all static and moving obstacles and has the minimum
completion time and the minimum distance traveled. In this model, the bounding
box around obstacles and robots is not considered, so the robot can move very
close to the obstacles without colliding with them. We considered two types of
obstacles: deterministic, which include all static obstacles such as walls that
do not move and all moving obstacles whose movements have a fixed pattern, and
non-deterministic, which include all obstacles whose movements can occur in any
direction with some probability distribution at any time. We also consider the
acceleration and deceleration of the robot to improve collision avoidance.
