  This paper introduces a collision avoidance system for navigating a
multicopter in cluttered outdoor environments based on the recent memory-less
motion planner, rectangular pyramid partitioning using integrated depth sensors
(RAPPIDS). The RAPPIDS motion planner generates collision-free flight
trajectories at high speed with low computational cost using only the latest
depth image. In this work we extend it to improve the performance of the
planner by taking the following issues into account. (a) Changes in the dynamic
characteristics of the multicopter that occur during flight, such as changes in
motor input/output characteristics due to battery voltage drop. (b) The noise
of the flight sensor, which can cause unwanted control input components. (c)
Planner utility function which may not be suitable for the cluttered
environment. Therefore, in this paper we introduce solutions to each of the
above problems and propose a system for the successful operation of the RAPPIDS
planner in an outdoor cluttered flight environment. At the end of the paper, we
validate the proposed method's effectiveness by presenting the flight
experiment results in a forest environment. A video can be found at
www.youtube.com/channel/UCK-gErmvZlBODN5gQpNcpsg
