Purpose

One of the development trends of robots is to enable robots to have the ability of anthropomorphic manipulation. Grasping is the first step of manipulation. For mobile manipulator robots, grasping a target during the movement process is extremely challenging, which requires the robots to make rapid motion planning for arms under uncertain dynamic disturbances. However, there are many situations require robots to grasp a target quickly while they move, such as emergency rescue. The purpose of this paper is to propose a method for target dynamic grasping during the movement of a robot.

Design/methodology/approach

An off-line learning from demonstrations method is applied to learn a basic reach model for arm and a motion model for fingers. An on-line dynamic adjustment method of arm speed for active and passive grasping mode is designed.

Findings

The experimental results of the robot movement on flat, slope and speed bumps ground show that the proposed method can effectively solve the problem of fast planning under uncertain disturbances caused by robot movement. The method performs well in the task of target dynamic grasping during the robot movement.

Originality/value

The main contribution of this paper is to propose a method to solve the problem of rapid motion planning of the robot arm under uncertain disturbances while the robot is grasping a target in the process of robot movement. The proposed method significantly improves the grasping efficiency of the robot in emergency situations. Experimental results show that the proposed method can effectively solve the problem.

中文翻译：

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基于学习方法的移动机器人运动过程中的目标动态抓取

目的

机器人的发展趋势之一是使机器人具有拟人化操纵的能力。抓取是操作的第一步。对于移动机械手机器人，在运动过程中抓住目标非常具有挑战性，这要求机器人在不确定的动态扰动下为手臂进行快速运动计划。但是，有很多情况需要机器人在移动时迅速抓住目标，例如紧急救援。本文的目的是提出一种在机器人运动过程中进行目标动态抓握的方法。

设计/方法/方法

通过演示的离线学习方法来学习手臂的基本触及模型和手指的运动模型。设计了主动和被动抓握方式的手臂速度在线动态调节方法。

发现

在平面，斜坡和减速带上机器人运动的实验结果表明，该方法可以有效解决机器人运动引起的不确定干扰下的快速规划问题。该方法在机器人运动过程中的目标动态抓取任务中表现良好。

创意/价值

本文的主要贡献是提出一种解决在不确定的干扰下机器人手臂在运动过程中抓取目标时快速规划手臂问题的方法。所提出的方法大大提高了机器人在紧急情况下的抓握效率。实验结果表明，该方法可以有效地解决该问题。