The focus of this dissertation is on incorporating robotics into pediatric cochlear implantation surgery. Since the 1980s, over 300,000 cochlear implantation surgeries have been performed worldwide, both in adults and children alike. For this dissertation research, surgical constraints in the operating theater are of utmost importance for the health and safety of the patient. As the field moves toward minimally invasive surgery, the issues that come with this, such as the loss of the natural field of view and the loss of tactile sense can create significant hurdles for surgeons. Medical robotics can be used to decrease the limitations of such surgical procedures since a desirable attribute of surgical robots is dexterity. Medical robotics can be used to can be used to counter these limitations, by taking advantage of the dexterity of surgical robots. These robots can be used in complex working environments for surgical procedures such as cochlear implantation surgery (CIS). The author's dissertation contains simulation, analytical, and numerical research, through which the effects of dynamics within the path planning algorithms on simulated and modeled cochlear implantation surgery have been studied. A novel path planning algorithm has been developed by making use of Rapidly-exploring Randomized Trees (RRT), and subsequently incorporating Sequential Quadratic Programming. The goal in utilizing a path planning algorithm (PPA) would be to increase safety and aid surgeons in a tightly constrained environment of pediatric temporal bone, which differs in geometry and size from adult temporal bones, and to positively impact the surgical procedure and recuperation from surgery. This algorithm was chosen for use in the tight spaces presented by pediatric patient anatomy and to address patient specific constraints or abnormalities that arise with cochlear implantation surgery in cases of congenital deafness, to add an extra layer of safety for patients. This method allows for more torque handling in tiny and heavily constrained environments, and prevents nicking of delicate anatomy, such as the cranial facial nerve, which can cause facial muscle paralysis if exposed to the slightest damage. The testing of the planning algorithm is carried out in a programming environment. These models are based on geometric equations describing the inner ear anatomy, based on data collected as a part of this dissertation work. Through this doctoral dissertation research, the author has developed several novel methods and innovative techniques to improve associated path planning algorithm. Since cochlear implantation surgeries are moving in the direction of minimally invasive surgery, it would be a beneficial goal to improve the surgery by including a path planning algorithm and a simulated robotic system to help reach the dissertation's goal of simulating the drilling done for cochlear implantation surgery, and with the ultimate goal of improving patient outcome and minimizing time to recovery.