Tabletop Pen Manipulation With a Vision-Guided 4-DoF Arm

📅 2026-08-16
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🤖 AI Summary
This study addresses the grasping limitations of low-cost 4-DOF manipulators lacking wrist rotation by proposing a vision-guided corrective sweeping strategy to substitute for missing hardware degrees of freedom. Integrating YOLO11n-OBB detection with adaptive motion planning, the system dynamically selects between direct grasping and reorientation based on object orientation to automate desktop stationery sorting. Experimental results demonstrate that this approach successfully corrects orientation deviations up to 90° across 326 trials. These findings validate the efficacy of algorithmic compensation for hardware deficiencies in achieving stable grasps of arbitrarily oriented objects, thereby establishing a novel paradigm for deploying cost-effective robotic arms in constrained manipulation tasks.
📝 Abstract
Low-cost four-degree-of-freedom (DoF) arms are among the most accessible robotic platforms. But they are, in theory, underactuated for picking up in situations where objects are at arbitrary orientations, a task that appears to require five degrees of freedom: the planar position (x and y), the height (z), a wrist rotation to align the gripper with the object, and gripper actuation, of which a four-DoF arm lacks the wrist rotation. This work shows that perception and motion planning can enable such an arm, a roughly $200 Waveshare RoArm-M2-S, under a fixed overhead camera to detect and color-sort writing utensils without that joint. A YOLO11n-OBB (You Only Look Once, oriented bounding box) detector locates each writing utensil; camera intrinsics and an ArUco reference pose convert its pixel coordinates to robot coordinates; and a color classifier labels it. The detected orientation angle determines the motion strategy: utensils close to the arm's fixed approach direction are picked up directly, and those at steeper angles are reoriented via corrective sweeps until they are graspable, after which they are picked up and sorted into the assigned color bin. Across 326 logged motions on seven writing utensils, the arm made 196 direct grasps and 130 corrective sweep passes, correcting misalignments up to 90 degrees, suggesting that clever task-informed engineering can compensate for a missing degree of freedom on tasks like this one.
Problem

Research questions and friction points this paper is trying to address.

4-DoF arm
underactuated manipulation
pen sorting
arbitrary orientation
missing degree of freedom
Innovation

Methods, ideas, or system contributions that make the work stand out.

Underactuated Manipulation
Corrective Sweeps
Vision-Guided Grasping
YOLO11n-OBB
Task-Informed Planning
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A
Anirudh Rangarajan
Dougherty Valley High School, 10550 Albion Road, San Ramon, California 94582, United States of America
Bibit Bianchini
Bibit Bianchini
Robotics PhD Student, University of Pennsylvania
roboticsmachine learningdynamics modelscontact models