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通过利用避障和其他限制来协调伸手和抓握动作。

Coordination of reaching and grasping by capitalizing on obstacle avoidance and other constraints.

作者信息

Rosenbaum D A, Meulenbroek R G, Vaughan J, Jansen C

机构信息

642 Moore Building, Department of Psychology, Pennsylvania State University, University Park, Pennsylvania 16802, USA,

出版信息

Exp Brain Res. 1999 Sep;128(1-2):92-100. doi: 10.1007/s002210050823.

Abstract

Reaching and grasping an object can be viewed as the solution of a multiple-constraint satisfaction problem. The constraints include contact with the object with the appropriate effectors in the correct positions as well as generation of a collision-free trajectory. We have developed a computational model that simulates reaching and grasping based on these notions. The model, rendered as an animation program, reproduces many basic features of the kinematics of human reaching and grasping behavior. The core assumptions of the model are: (1) tasks are defined by flexibly organized constraint hierarchies; (2) manual positioning acts, including prehension acts, are first specified with respect to goal postures and then are specified with respect to movements towards those goal postures; (3) goal postures are found by identifying the stored posture that is most promising for the task, as determined by the constraint hierarchy, and then by generating postures that are more and more dissimilar to the most-promising stored posture until a deadline is reached, at which time the best posture that was found during the search is defined as the goal posture; (4) depending on when the best posture was encountered in the search, the deadline for the search in the next trial is either increased or decreased; (5) specification of a movement to the goal posture begins with straight-line interpolation in joint space between the starting posture and goal posture; (6) if an internal simulation of this default movement suggests that it will result in collision with an obstacle, the movement can be reshaped until an acceptable movement is found or until time runs out; (7) movement reshaping occurs by identifying a via posture that serves as a body position to which the actor moves from the starting posture and then back to the starting posture, while simultaneously making the main movement from the starting posture to the goal posture; (8) the via posture is identified using the same posture-generating algorithm as used to identify the goal posture. These processes are used both for arm positioning and, with some elaboration, for prehension. The model solves a number of problems with an earlier model, although it leaves some other problems unresolved.

摘要

伸手去够并抓取一个物体可以被视为一个多重约束满足问题的解决方案。这些约束包括使用正确位置的合适效应器与物体接触,以及生成无碰撞轨迹。我们基于这些概念开发了一个计算模型。该模型以动画程序呈现,再现了人类伸手和抓取行为运动学的许多基本特征。该模型的核心假设是:(1)任务由灵活组织的约束层次结构定义;(2)手动定位动作,包括抓握动作,首先相对于目标姿势进行指定,然后相对于朝向那些目标姿势的运动进行指定;(3)通过识别存储的姿势来找到目标姿势,该姿势由约束层次结构确定,对于该任务最有希望,然后生成与最有希望的存储姿势越来越不同的姿势,直到达到截止时间,此时在搜索过程中找到的最佳姿势被定义为目标姿势;(4)根据在搜索中遇到最佳姿势的时间,下一次试验的搜索截止时间要么增加要么减少;(5)向目标姿势的运动指定从起始姿势和目标姿势之间的关节空间中的直线插值开始;(6)如果对该默认运动的内部模拟表明它将导致与障碍物碰撞,则可以对运动进行重塑,直到找到可接受的运动或直到时间用完;(7)运动重塑通过识别一个中间姿势来实现,该中间姿势用作身体位置,演员从起始姿势移动到该位置然后再回到起始姿势,同时进行从起始姿势到目标姿势的主要运动;(8)使用与用于识别目标姿势相同的姿势生成算法来识别中间姿势。这些过程既用于手臂定位,经过一些细化后也用于抓握。该模型解决了早期模型的一些问题,尽管它还留下了一些其他未解决的问题。

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