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STEMbot: A Compliant Robot for Under-Canopy Plant Navigation

Summary

STEMbot is a miniature climbing robot designed for autonomous navigation under plant canopies to enable early pest detection. It integrates PIN-SLAM and a semantic OcTree, and uses a manifold-constrained A* planner, demonstrating reliable traversal on stems of 7-33mm with reconstruction accuracy under 1cm.

SourcearXiv RoboticsAuthor: Zachary Charlick, Nilay Roy Choudhury, Haoyu Ma, Xiaonan Huang, Dmitry Berenson
STEMbot: A Compliant Robot for Under-Canopy Plant Navigation
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[Submitted on 8 Jul 2026]

Title:STEMbot: A Compliant Robot for Under-Canopy Plant Navigation

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Abstract:The scalability of organic agriculture is partially limited by the labor costs associated with monitoring for pests. While drones and rovers are well-suited for agricultural monitoring from above or next to plants, many pests live on the underside of leaves or on plant stems, making them detectable only after they have caused significant damage. To enable early pest detection we present STEMbot, a miniature climbing robot system designed for autonomous navigation under plant canopies. Unlike existing climbing platforms that lack on-board perception or are restricted to unbranched vertical trunks, STEMbot integrates a fully geometric PIN-SLAM pipeline with a semantic OcTree to achieve robust localization and mapping while climbing the plant. To plan STEMbot's motion we propose a manifold-constrained A* planner along with ray-tracing goal specification to enable branch-aware traversal and the inspection of occluded targets. We validate our system through hardware experiments, demonstrating reliable traversal of stems ranging from 7-33mm and autonomous navigation across four distinct plant specimens. Quantitative evaluations show that our system achieves high-fidelity geometric reconstructions with an average Chamfer distance of less than 1cm relative to an offline photogrammetry baseline, confirming that STEMbot maintains the globally consistent odometry needed for autonomous navigation.

Comments: Accepted to the 2026 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2026). Project page: this https URL

Subjects:

Robotics (cs.RO)

Cite as: arXiv:2607.07873 [cs.RO]

(or arXiv:2607.07873v1 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2607.07873

arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Zachary Charlick [view email] [v1] Wed, 8 Jul 2026 19:17:40 UTC (4,888 KB)

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Key points

  • Addresses labor cost in organic farming by enabling early pest detection under canopy.
  • Combines geometric PIN-SLAM with semantic OcTree for robust localization and mapping.
  • Manifold-constrained A* planner with ray-tracing goal specification for branch-aware traversal.
  • Hardware experiments show reliable stem climbing on diverse plants; Chamfer distance <1cm from photogrammetry baseline.

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