Control Architecture for Safe Grasping of Fragile Objects Using a Coarse Position-Controlled Gripper

• URL: http://arxiv.org/abs/2609.12737v1
• Date: Fri, 11 Sep 2026 11:37:40 GMT
• Title: Control Architecture for Safe Grasping of Fragile Objects Using a Coarse Position-Controlled Gripper
• Abstract summary: We present a force/torque-based contact estimation method for a coarse position-controlled gripper.<n>The desired contact forces are estimated online to keep stable contact with objects of unknown properties.<n> Experiments show that the proposed algorithm not only prevents slippage but also applies minimal force to safely grasp an object.
• Score: 0.26999000177990923
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Robots are increasingly used in unstructured environments. The need for them to safely grasp unknown objects without damaging them becomes crucial. Humans achieve this by sensing and quickly responding by adjusting their grasping force. Similarly, effective grasp acquisition in robots requires compliant interaction strategies that can adapt to uncertain object properties and adjust to any instabilities during manipulation. We present a geometry-aware force/torque-based contact estimation method for a coarse position-controlled gripper, combined with an adaptive admittance controller for safe grasp acquisition. The desired contact forces are estimated online to keep stable contact with objects of unknown properties. This enables compliant and stable grasps while avoiding excessive forces. Experiments with objects of different sizes, shapes, stiffnesses, and weights show that the proposed algorithm not only prevents slippage but also applies minimal force to safely grasp an object without causing excessive deformation.

Related papers

• SoftVTBench: A Safety-Aware Visuo-Tactile Benchmark for Physically Constrained Robotic Manipulation of Deformable Objects [56.16187327142104]
  We present SoftVTBench, a safety-aware visuo-tactile benchmark for deformable object manipulation.<n>Built in Isaac Sim with finite-element-simulated deformable objects, SoftVTBench provides multi-view RGB observations, tactile sensing with marker motion, proprioception, and language instructions.
  arXiv  Detail & Related papers  (2026-07-05T11:12:29Z)
• Current as Touch: Proprioceptive Contact Feedback for Compliant Dexterous Manipulation [21.695801136739558]
  We propose a proprioception-driven framework that learns contact-aware compliance cues from motor current and joint states.<n>Our method predicts a compliance reference position: an ideal joint-position target for a standard PD controller.<n>Experiments show stable compliant grasping, safer and more efficient teleoperation, and improved downstream policy learning without external tactile or force sensors.
  arXiv  Detail & Related papers  (2026-07-03T17:59:50Z)
• Grasp-Oriented Non-Prehensile Manipulation via Learning a Graspability Field [53.59810543538279]
  Non-prehensile manipulation is often used as a preparatory step for robotic grasping.<n>In practice, objects admit multiple graspable configurations and the desired pose is not known in advance.<n>We reformulate non-prehensile manipulation for grasping as optimizing an object centric graspability objective.
  arXiv  Detail & Related papers  (2026-06-29T15:33:27Z)
• Industrial Dual-Arm Box Handling via Online Inertial Estimation and Convex Wrench Optimization [5.026843146697991]
  Industrial robotic object handling often involves boxes and packages whose mass and center of mass are not known in advance.<n>This paper presents a friction-aware dual-arm box-handling framework for objects with unknown inertial properties.
  arXiv  Detail & Related papers  (2026-05-21T05:40:59Z)
• Learning Reactive Dexterous Grasping via Hierarchical Task-Space RL Planning and Joint-Space QP Control [50.28263951510334]
  We propose a hybrid hierarchical control framework for reactive dexterous grasping.<n>The proposed framework explicitly decouples high-level spatial intent from low-level joint execution.<n>We extensively validate the proposed framework through a rigorous simulation-to-reality pipeline.
  arXiv  Detail & Related papers  (2026-05-05T04:49:38Z)
• Rigidity-Based Multi-Finger Coordination for Precise In-Hand Manipulation of Force-Sensitive Objects [5.313029497667778]
  Multi-fingered hands rely solely on fingertip point contacts and are not able to apply pull forces.<n>We propose a dual-layer framework for multi-finger coordination, enabling high-precision manipulation of force-sensitive objects.<n>We validate the framework on a custom dexterous hand, demonstrating the capability to manipulate fragile objects.
  arXiv  Detail & Related papers  (2026-02-15T11:40:39Z)
• A Precise Real-Time Force-Aware Grasping System for Robust Aerial Manipulation [5.804333840515478]
  Aerial manipulation requires force-aware capabilities to enable safe and effective grasping and physical interaction.<n>We propose a novel force-aware grasping framework incorporating six low-cost, sensitive skin-like tactile sensors.<n>The proposed framework enables precise force-aware grasping control, allowing safe manipulation of fragile objects and real-time weight measurement of grasped items.
  arXiv  Detail & Related papers  (2026-02-09T12:40:34Z)
• UniForce: A Unified Latent Force Model for Robot Manipulation with Diverse Tactile Sensors [51.88112610411651]
  We propose a novel unified tactile representation learning framework that learns a shared latent force space across diverse tactile sensors.<n>UniForce reduces cross-sensor domain shift by jointly modeling inverse dynamics (image-to-force) and forward dynamics (force-to-image)<n>To avoid reliance on expensive external force/torque (F/T) sensors, we exploit static equilibrium and collect force-paired data via direct sensor--object--sensor interactions.
  arXiv  Detail & Related papers  (2026-02-01T11:03:01Z)
• An Adaptive Grasping Force Tracking Strategy for Nonlinear and Time-Varying Object Behaviors [7.059232979003729]
  This paper introduces the concept of generalized stiffness, extending the definition of stiffness to nonlinear time-varying grasp system models.<n>The proposed method achieves high precision and short probing time, while showing better adaptability to non-ideal objects.
  arXiv  Detail & Related papers  (2024-12-03T09:55:00Z)
• Tactile Estimation of Extrinsic Contact Patch for Stable Placement [64.06243248525823]
  We present the design of feedback skills for robots that must learn to stack complex-shaped objects on top of each other. We estimate the contact patch between a grasped object and its environment using force and tactile observations.
  arXiv  Detail & Related papers  (2023-09-25T21:51:48Z)
• Learning Compliance Adaptation in Contact-Rich Manipulation [81.40695846555955]
  We propose a novel approach for learning predictive models of force profiles required for contact-rich tasks. The approach combines an anomaly detection based on Bidirectional Gated Recurrent Units (Bi-GRU) and an adaptive force/impedance controller.
  arXiv  Detail & Related papers  (2020-05-01T05:23:34Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.