Bionics are robots made by electronics-mechanical techniques. Bionics need to move in optimal path in order to accomplish the task. Sometimes, the robots have to traverse through complicated paths which involve hindrances. The paths are needed to be optimized in order to reduce expenses while traversing on routes. This paper proposes a path planning technique for Bionic by incorporating the nature inspired Ant Colony Algorithm (ACA). ACA is motivated by the foraging behavior of ants. The ACA has the ability to find optimal paths in various similar domain problems. The system creates ants influenced by the behavior of real ants. The ant lay down a chemical called as pheromone while traveling on paths. Dynamic pheromone updates play crucial role to handle changing conditions in environment. It also helps in the development of a heuristic function to guide the ants toward better routes having collision-free paths. The adaptability of algorithm is further enhanced by the addition of a mechanism for adjustment of the exploration–exploitation property of pheromone. To evaluate the performance of the proposed approach, the simulations and experiments are conducted. Comparative analyses are also conducted with traditional path planning methods to demonstrate the betterment of the Ant Colony Algorithm in terms of path optimization and to reduce the standard deviation of time to complete the path.