Full title: Towards Autonomous Robotic Precision Harvesting: Mapping, Localization, Planning and Control for a Legged Tree Harvester
We present an integrated system for performing precision harvesting missions using a legged harvester (HEAP) in a confined, GPS denied forest environment. The mission starts with a human mapping the area of interest using a custom-made sensor module. Subsequently, a human expert selects the trees for harvesting. The sensor module is then mounted on the machine and used for localization within the given map. 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. Our system has been tested on a testing field with tree trunks and in a natural forest.
The paper can be found on arxiv:
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Code available at:
Planning & path tracking:
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Heightmap generation:
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Localization:
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Tree detection:
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This research was partially supported by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme grant agreement No 852044 and through the SNSF National Centre of Competence in Digital Fabrication (NCCR dfab).
