Bio-Robotics : Elastic Strip Framework

Most motion planning algorithms assume complete knowledge of the geometry of environment.  Typically obstacles in the environment are assumed to be static or their motion is known as a function of time.  To generate a motion, the algorithm performs a search in the configuration space of the robot, C..  Such a space encapsulates all legal, Cfree , and illegal, Cobs, configurations of the robot and the goal is to find a continuous path in Cfree connecting initial and final configurations.  For robots with multiple degrees of freedom, the configuration space is extremely high-dimensional.  To allow planning for environments with moving obstacles the configuration space must be further augmented by the dimension of time.  Performing a search in such high-dimensional spaces is infeasible and people have in the past resorted to probabilistic and randomized approaches that confine the search space to a subset of all possible configurations. Continue reading