Industrial manipulators often interact with large and complex objects for a variety of automation tasks. Finding a feasible path for the robot end-effector that ensures task success is often non-trivial due to considerations such as reachability, singularity avoidance, and collision avoidance. This paper proposes an approach to expand the search space for feasible robot trajectories (and search for an optimal solution) by taking advantage of task redundancy for certain tasks while ensuring task completion. The effort builds on previous work enabling virtual fixture generation for complex shapes given CAD or scan data. The proposed method has been developed into a trajectory planning library on the ROS (Robot Operating System) framework and tested by simulating an interaction of a six-axis industrial robot with an aircraft fuselage. Results show increased coverage of task area with minimal robot base placements.

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