  When executing a certain task, human beings can choose or make an appropriate
tool to achieve the task. This research especially addresses the optimization
of tool shape for robotic tool-use. We propose a method in which a robot
obtains an optimized tool shape, tool trajectory, or both, depending on a given
task. The feature of our method is that a transition of the task state when the
robot moves a certain tool along a certain trajectory is represented by a deep
neural network. We applied this method to object manipulation tasks on a 2D
plane, and verified that appropriate tool shapes are generated by using this
novel method.
