The independent movement of robotics in uncontrollable situations is difficult since it necessitates the cooperation of several components. It necessitates simultaneously creating a map for the surroundings, locating the robot inside that map, creating a motion schedule based on the map, implementing that schedule with the controllers, as well as other operations. The automated navigational issue, on either side, is critical for the growth of robots. Delivering packages, agriculture, search and relief, cleaning, monitoring, construction, and shipping are just a few of the applications which require this challenge to be handled. All of such applications take place in unregulated conditions. A sophisticated cognition process is required to detect and respond to an uncertain place. There seem to be movable robots that can run, walk, leap, and perform other actions similar to their natural counterparts. The future of robotic systems, comprising the latest trends, is covered in this study. To prevent having to reanalyze a whole course in response to a variation in human nature, the controller should permit local deformation or acceleration/deceleration by altering the time variable. The trajectories controller must always be willing to change from an early course to a newer one. Cubic polynomial variables are now employed to characterize motions because they are smooth, flexible, and easy to compute. Furthermore, smoothing algorithms are suggested to present and analyze the essential ideas of Free Space, Given Space, and Unidentified Space Assertions to handle incomplete visibility of the surroundings to meet the aesthetic goal. To travel in variable and uncertain situations, these premises are required. We present the first two strategies for recovering from misleading barriers in the mapping and causing the robots to keep looking for their target in variable surroundings. We offer a strategy for navigating more effectively in unfamiliar situations.