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This paper presents an integrated system for performing precision harvestingmissions using a legged harvester. Our harvester performs a challenging task ofautonomous navigation and tree grabbing in a confined, GPS denied forestenvironment. Strategies for mapping, localization, planning, and control areproposed and integrated into a fully autonomous system. The mission starts witha human mapping the area of interest using a custom-made sensor module.Subsequently, a human expert selects the trees for harvesting. The sensormodule is then mounted on the machine and used for localization within thegiven map. A planning algorithm searches for both an approach pose and a pathin a single path planning problem. We design a path following controllerleveraging the legged harvester's capabilities for negotiating rough terrain.Upon reaching the approach pose, the machine grabs a tree with ageneral-purpose gripper. This process repeats for all the trees selected by theoperator. Our system has been tested on a testing field with tree trunks and ina natural forest. To the best of our knowledge, this is the first time thislevel of autonomy has been shown on a full-size hydraulic machine operating ina realistic environment.

Towards Autonomous Robotic Precision Harvesting: Mapping, Localization, Planning and Control for a Legged Tree Harvester