  The Rapidly-exploring Random Tree (RRT) algorithm has been one of the most
prevalent and popular motion-planning techniques for two decades now.
Surprisingly, in spite of its centrality, there has been an active debate under
which conditions RRT is probabilistically complete. We provide two new proofs
of probabilistic completeness (PC) of RRT with a reduced set of assumptions.
The first one for the purely geometric setting, where we only require that the
solution path has a certain clearance from the obstacles. For the kinodynamic
case with forward propagation of random controls and duration, we only consider
in addition mild Lipschitz-continuity conditions. These proofs fill a gap in
the study of RRT itself. They also lay sound foundations for a variety of more
recent and alternative sampling-based methods, whose PC property relies on that
of RRT.
  Our original publication contains an error in the analysis of the case of the
kinodynamic RRT. Here, we rectify the problem by modifying the proof of Theorem
2, which, in particular, necessitated a revision of Lemma 3. Briefly, the
original (and erroneous) proof of Theorem 2 used a sequence of equal-size
balls. The correction uses a sequence of balls of increasing radii. We
emphasize that the correction is in Lemma 3 and the proof of Theorem 2 only.
The main results remain unchanged.
