Scholarlink

<p>The high-dimensional characteristics of dexterous hands make the grasping posture solving process complex. In particular, achieving optimal grasping under multi-point contact for objects of different shapes remains a challenging task. To address this issue, this paper proposes a grasping posture planning (ICGPP) method that combines an improved angle lizard optimization algorithm with Coppeliasim simulation. This method follows the criterion of “minimum force–minimum angle” and utilizes simulated tactile information to optimize grasping postures. We constructed a virtual dexterous hand with pressure sensors on the Coppeliasim simulation platform to provide multi-point contact feedback for the proposed improved angle lizard optimization algorithm (IHLOA), thereby solving the optimal joint angle matrix. Results from both simulation and physical experiments demonstrate that the method can effectively generate enveloping, precise, and hybrid grasping postures that meet the optimization criteria, achieving stable and efficient grasping of objects with different shapes.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Grasping posture planning method for five-fingered dexterous hands based on the minimum force–minimum angle criterion

  • 期刊论文

  • 发表日期：

    2026年4月9日

查看全文
  • Yinfeng Geng,
  • Yubo Fan,
  • Qiaoling Du,
  • Wenli Ma,
  • Zhenlong Bi

摘要

The high-dimensional characteristics of dexterous hands make the grasping posture solving process complex. In particular, achieving optimal grasping under multi-point contact for objects of different shapes remains a challenging task. To address this issue, this paper proposes a grasping posture planning (ICGPP) method that combines an improved angle lizard optimization algorithm with Coppeliasim simulation. This method follows the criterion of “minimum force–minimum angle” and utilizes simulated tactile information to optimize grasping postures. We constructed a virtual dexterous hand with pressure sensors on the Coppeliasim simulation platform to provide multi-point contact feedback for the proposed improved angle lizard optimization algorithm (IHLOA), thereby solving the optimal joint angle matrix. Results from both simulation and physical experiments demonstrate that the method can effectively generate enveloping, precise, and hybrid grasping postures that meet the optimization criteria, achieving stable and efficient grasping of objects with different shapes.