In the previous work of the authors, a modified version of Rapidly exploring Randomized Trees (RRT) algorithm was used to study trajectories of end effectors of multi-link robotic systems. They showed how constraints could be used for better trajectory control. The overall aim of the prior work and the current study is to develop path-planning algorithms that can be used for robots in surgical environments. The authors have picked the KUKA DLR LWR IV+, a seven link, 7 Degree of Freedom (DOF) system, as a representative system for their studies. In the current study, as an initial step, obstacle avoidance has been examined for systems with low number of degrees of freedom (DOF). The goal of using obstacle avoidance is to navigate to representative anatomical body parts such as veins or bones. The authors have explored motions of multi-link robotic systems, by combining the RRT algorithm with Obstacle Avoidance. The modified path-planning algorithm is expected to yield smooth trajectories, which can be followed to expertly navigate delicate anatomical obstacles between initial and goal states. This is facilitated through the construction of constraints that can capture the difficulties encountered during minimally invasive and laparo-scopic surgical procedures. These constraints, which have been formulated based on discussions with multiple surgeons, are utilized for planning the movement of the system. The motion simulations are intended to better represent the confining environment of the human body during surgical procedures, in particular, such as those involved in cochlear implantation. It will be discussed as to how well the formulated constraints help in the realizing paths for the robot end effectors. Given the manner in which the motion-planning algorithm has been constructed with information from the operating theatre, it is expected that this planning algorithm will be uniquely suited for the surgical environment.

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