Reactive grasp controller for dynamic grasping of moving objects

Robots are not yet ready to handle unstructured and uncertain environments by adapting their trajectory online depending on the changes in the surroundings. Knowing how to handle moving objects is an essential skill for robots in many industrial and service robotics applications. This work presents a reactive grasp controller inspired by an established human motion model. It starts planning by generating a straight line from the current pose of the end-effector to the target object pose. Then, the line is shaped considering the new target position. A trace controller guarantees that the end-effector remains on the path, and the collision-aware velocity regulation feature ensures to safely proceed on it by modulating the advancing velocity until completely stopping the motion if an obstacle is encountered on the path toward the target pose goal. Control actions are sent to the robot controller as smooth velocity commands at 1 KHz to be reactive. The capabilities of the proposed planner are showcased on a real robot in three dynamic experimental settings relevant to industry: (i) grasping objects moving on a conveyor belt, and two human–robot collaboration tasks that are (ii) grasping objects that can move during the robot’s motion toward the target due to the interaction of a human operation, and (iii) human-to-robot handover. A comparison with state-of-the-art methods is also discussed.

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Publication Details

Journal
Robotics and Autonomous Systems
Published
2026-02-24
DOI
https://doi.org/10.1016/j.robot.2026.105401
Primary Topic
Robot Manipulation and Learning
Type
article
Field-Weighted Citation Impact
0.00
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article

Reactive grasp controller for dynamic grasping of moving objects

Emilio Maranci, Salvatore D’Avella, Carlo Alberto Avizzano
Robotics and Autonomous Systems
Robot Manipulation and Learning
article

Reactive grasp controller for dynamic grasping of moving objects

Emilio Maranci, Salvatore D’Avella, Carlo Alberto Avizzano
article en

Abstract

Robots are not yet ready to handle unstructured and uncertain environments by adapting their trajectory online depending on the changes in the surroundings. Knowing how to handle moving objects is an essential skill for robots in many industrial and service robotics applications. This work presents a reactive grasp controller inspired by an established human motion model. It starts planning by generating a straight line from the current pose of the end-effector to the target object pose. Then, the line is shaped considering the new target position. A trace controller guarantees that the end-effector remains on the path, and the collision-aware velocity regulation feature ensures to safely proceed on it by modulating the advancing velocity until completely stopping the motion if an obstacle is encountered on the path toward the target pose goal. Control actions are sent to the robot controller as smooth velocity commands at 1 KHz to be reactive. The capabilities of the proposed planner are showcased on a real robot in three dynamic experimental settings relevant to industry: (i) grasping objects moving on a conveyor belt, and two human–robot collaboration tasks that are (ii) grasping objects that can move during the robot’s motion toward the target due to the interaction of a human operation, and (iii) human-to-robot handover. A comparison with state-of-the-art methods is also discussed.

Robotics and Autonomous SystemsVol. 200
Scuola Superiore Sant'Anna (IT)
Openalex Percentile: Top 47%
Robot Manipulation and Learning
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