  In this paper, we propose a novel inverse Dynamic Reachability Map (iDRM)
that allows a floating base system to find valid end-poses in complex and
dynamically changing environments in real-time. End-pose planning for valid
stance pose and collision-free configuration is an essential problem for
humanoid applications, such as providing goal states for walking and motion
planners. However, this is non-trivial in complex environments, where standing
locations and reaching postures are restricted by obstacles. Our proposed iDRM
customizes the robot-to-workspace occupation list and uses an online update
algorithm to enable efficient reconstruction of the reachability map to
guarantee that the selected end-poses are always collision-free. The iDRM was
evaluated in a variety of reaching tasks using the 38 degree-of-freedom (DoF)
humanoid robot Valkyrie. Our results show that the approach is capable of
finding valid end-poses in a fraction of a second. Significantly, we also
demonstrate that motion planning algorithms integrating our end-pose planning
method are more efficient than those not utilizing this technique.
