The increasing use of mobile robots in everyday life has ne- cessitated the development of efficient path planning algo- rithms to enable safe and reliable navigation in both known and unknown environments. Path planning is the process of discovering an optimal and safe path for a robot to navigate from its starting point to its destination. Finding the ideal collision-free path is one of the most challenging aspects of mobile robot navigation. There are various path-planning techniques to obtain an optimal path in the presence of ob- stacles; an optimal path planning technique of mobile robot saves time and reduces capital investment. These techniques can be divided into two categories viz clas- sical and heuristic. This paper provides a comprehensive re- view of path planning techniques for mobile robot naviga- tion in known and unknown environments. Path planning becomes more challenging in unknown environments, where a robot does not have prior knowledge about the surround- ings. In contrast, path planning in known environments can utilize prior knowledge about the environment to find an op- timal path. When comparing classical and heuristic approaches, it has been found that heuristic approaches are more resilient and perform well in all environments because they can deal with uncertainties. Heuristic approaches are also employed as hybrid algorithms to increase the performance of the clas- sical approaches. Heuristic techniques are well-known and frequently used for mobile robot path planning. Key opti- mization criteria, including path length, smoothness and safety degree, are also critically assessed. The paper also tabulates the advantages, disadvantages, and comparison of classical and heuristic path-planning techniques. The paper finally concludes by discussing potential future research directions to provide a roadmap for future advancements in mobile robot path planning techniques