日本フィジカルAI新聞

世界のフィジカルAIを、日本語で。

マニピュレーションarXiv:2611.13268

矩形物体の協調マルチロボット押し操作におけるフォースクロージャ条件

Force-Closure Condition for Cooperative Multi-robot Pushing of Rectangular Objects

シェア:XThreadsFacebookLINEはてブBluesky

4つの無摩擦接触点で矩形物体を押す際の力学的閉包条件を閉形式で導出し、接触配置の調整則と軌道追従制御への統合を示した研究。

著者: Duy Anh Nguyen, Trung Dung Ngo

分類: cs.RO, eess.SY

原文アブストラクト

In cooperative object manipulation, the placement of pushing contacts determines whether force closure can be achieved and agents can generate arbitrary forces and torques on the object correspondingly. This study derives a necessary and sufficient closed-form condition for the planar force closure of a rectangular object, a common object shape in everyday settings, under four frictionless pushing contacts. For a rectangle of length $b$ and width $a$, force closure holds if and only if $(l_1+l_3-b)(l_2+l_4-a)<0$, where $l_1,l_2,l_3,l_4$ are the four edge contact locations. This condition is independent of the object's center of mass and is used to verify contact configurations before contact force allocation. When the condition is not satisfied, the signs of the two factors indicate which opposing contact pair should be adjusted. The condition and adjustment rule are then integrated into a full-pose trajectory-tracking framework as a geometric feasibility layer to demonstrate their use in control. Static wrench feasibility tests validate the proposed condition, while narrow-passage floating-body simulations show that maintaining a force-closure configuration reduces the RMS tracking errors in $x$, $y$, and unwrapped yaw from $12.05$ m, $18.11$ m, and $535.96^\circ$ to $2.24$ m, $2.66$ m, and $2.69^\circ$, respectively.

関連論文

  1. 1パナソニックHDら、ロボット操作AI「T-Rex」を共同開発 12タスクで平均成功率65%研究・技術
  2. 2Hugging Face、ロボット学習基盤「LeRobot v0.7.0」を公開 対話操作と大規模データ学習に対応新製品・発表
  3. 3NVIDIA、Vera CPUのエージェント処理性能を公表 x86比で速度・電力効率を比較半導体・GPU
  4. 4Agility、SPAC合併でナスダック上場資金調達
  5. 5AgiBot、基盤モデル「GO-3 Preview」を発表 身体性AIの3ベンチマークで首位新製品・発表
PR本紙発行元 EmplifAI