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相关论文: Analytical Solution for Inverse Kinematics

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We present an analytical solution for the inverse kinematics (IK) of a robotic arm with one prismatic joint and four revolute joints. This 5-DoF design is a result of minimizing weight while preserving functionality of the device in a…

机器人学 · 计算机科学 2020-11-17 Vighnesh Vatsal , Guy Hoffman

Inverse Kinematics (IK) solves the problem of mapping from the Cartesian space to the joint configuration space of a robotic arm. It has a wide range of applications in areas such as computer graphics, protein structure prediction, and…

机器人学 · 计算机科学 2022-08-30 Chi-Kai Ho , Chung-Ta King

The Inverse Kinematics (IK) problem is to nd robot control parameters to bring it into the desired position under the kinematics and collision constraints. We present a global solution to the optimal IK problem for a general serial 7DOF…

机器人学 · 计算机科学 2020-07-27 Pavel Trutman , Safey El Din Mohab , Didier Henrion , Tomas Pajdla

This paper presents an analytical solution to the inverse kinematic problem(IKP) for the seven degree-of-freedom (7-DOF) Moz1 Robot Arm with offsets on wrist. We provide closed-form solutions with the novel arm angle . it allow fully…

机器人学 · 计算机科学 2026-02-05 Ke Chen

Solving the analytical inverse kinematics (IK) of redundant manipulators in real time is a difficult problem in robotics since its solution for a given target pose is not unique. Moreover, choosing the optimal IK solution with respect to…

机器人学 · 计算机科学 2023-03-28 Minh Nhat Vu , Florian Beck , Michael Schwegel , Christian Hartl-Nesic , Anh Nguyen , Andreas Kugi

We propose an effective method for solving the inverse kinematic problem of a specific model of 6-degree-of-freedom (6-DOF) robot manipulator using computer algebra. It is known that when the rotation axes of three consecutive rotational…

机器人学 · 计算机科学 2025-09-09 Takumu Okazaki , Akira Terui , Masahiko Mikawa

Near kinematic singularities of a serial manipulator, the inverse kinematics (IK) problem becomes ill-conditioned, which poses computational problems for the numerical solution. Computational methods to tackle this issue are based on…

机器人学 · 计算机科学 2024-12-31 Andreas Mueller

Numerical methods for Inverse Kinematics (IK) employ iterative, linear approximations of the IK until the end-effector is brought from its initial pose to the desired final pose. These methods require the computation of the Jacobian of the…

机器人学 · 计算机科学 2023-08-08 Jacket Demby's , Jeffrey Uhlmann , Guilherme N. DeSouza

Analytic and optimization methods for solving inverse kinematics (IK) problems have been deeply studied throughout the history of robotics. The two strategies have complementary strengths and weaknesses, but developing a unified approach to…

机器人学 · 计算机科学 2026-02-06 Thomas Cohn , Lihan Tang , Alexandre Amice , Russ Tedrake

Calculating the inverse kinematics (IK) is a fundamental challenge in robotics. Compared to numerical or learning-based approaches, analytical IK provides higher efficiency and accuracy. However, existing analytical approaches are difficult…

机器人学 · 计算机科学 2025-08-22 Daniel Ostermeier , Jonathan Külz , Matthias Althoff

The majority of inverse kinematics (IK) algorithms search for solutions in a configuration space defined by joint angles. However, the kinematics of many robots can also be described in terms of distances between rigidly-attached points,…

机器人学 · 计算机科学 2022-07-06 Filip Marić , Matthew Giamou , Ivan Petrović , Jonathan Kelly

Continuum manipulators have gained significant attention as a promising alternative to rigid manipulators, offering notable advantages in terms of flexibility and adaptability within intricate workspace. However, the broader application of…

机器人学 · 计算机科学 2024-10-29 Yinan Sun , Sai Wang

Inverse kinematics (IK) is the problem of finding robot joint configurations that satisfy constraints on the position or pose of one or more end-effectors. For robots with redundant degrees of freedom, there is often an infinite, nonconvex…

Inverse Kinematics (IK) remains a dynamic field of research, with various methods striving for speed and precision. Despite advancements, many IK techniques face significant challenges, including high computational demands and the risk of…

机器人学 · 计算机科学 2024-09-16 Zineb Benhmidouch , Saad Moufid , Aissam Ait Omar

Robotic tasks, like reaching a pre-grasp configuration, are specified in the end effector space or task space, whereas, robot motion is controlled in joint space. Because of inherent actuation errors in joint space, robots cannot achieve…

机器人学 · 计算机科学 2019-10-25 Anirban Sinha , Nilanjan Chakraborty

As the pace of AI technology continues to accelerate, more tools have become available to researchers to solve longstanding problems, Hybrid approaches available today continue to push the computational limits of efficiency and precision.…

机器人学 · 计算机科学 2024-06-21 Enoch Adediran , Salem Ameen

The general inverse kinematics (IK) problem of a manipulator, namely that of acquiring the self-motion manifold (SMM) of all admissible joint angles for a desired end-effector pose, plays a vital role in robotics modeling, planning and…

机器人学 · 计算机科学 2021-04-27 Yajue Yang , Yuanqing Wu , Jia Pan

This paper presents the open-source robot inverse kinematics (IK) solver IK-Geo, the fastest general IK solver based on published literature. In this unifying approach, IK for any 6-DOF all-revolute (6R) manipulator is decomposed into six…

机器人学 · 计算机科学 2024-02-20 Alexander J. Elias , John T. Wen

Computer vision/deep learning-based 3D human pose estimation methods aim to localize human joints from images and videos. Pose representation is normally limited to 3D joint positional/translational degrees of freedom (3DOFs), however, a…

计算机视觉与模式识别 · 计算机科学 2022-09-07 Kevin Gildea , Clara Mercadal-Baudart , Richard Blythman , Aljosa Smolic , Ciaran Simms

The inverse kinematics (IK) problem of continuum robots has been investigated in depth in the past decades. Under the constant-curvature bending assumption, closed-form IK solution has been obtained for continuum robots with variable…

机器人学 · 计算机科学 2021-10-06 Yifan Wang , Zhonghao Wu , Longfei Wang , Bo Feng , Kai Xu
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