  This paper presents an integrated system for performing precision harvesting
missions using a walking harvester. Our harvester performs the challenging task
of autonomous navigation and tree grabbing in a confined, GPS denied forest
environment. Strategies for mapping, localization, planning, and control are
proposed and integrated into a fully autonomous system. The mission starts with
a human or a mobile robot mapping the area of interest using a custom-made
sensor module. Subsequently, a human expert or a data-supported algorithm
selects the trees for harvesting. The sensor module is then mounted on the
machine and used for localization within the given map. A planning algorithm
searches for both an approach pose and a path in a single path planning
problem. We design a path following controller leveraging the walking
harvester's capabilities for negotiating rough terrain. Upon reaching the
approach pose, the machine grabs a tree with a general-purpose gripper. This
process repeats for all the trees selected by the operator (algorithm). Our
system has been tested on a testing field with tree trunks and in a natural
forest. To the best of our knowledge, this is the first time this level of
autonomy has been shown on a full-size hydraulic machine operating in a
realistic environment.
