Implementation of KDL Inverse Kinematics Routine on the Atlas Humanoid Robot

Khokar, Karan; Beeson, Patrick; Burridge, Rob

doi:10.1016/j.procs.2015.02.063

Cited by 17 publications

(8 citation statements)

References 2 publications

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“…On the other hand, in addition to the hand-made controlling boards, commercial controlling boards are used extensively. In this way, Raspberry Pi boards (Mejías et al, 2017), ARMbased boards (Almubarak & Tadesse, 2017), compatible Arduino boards (Al-Busaidi, 2012), or off-board computing controls (Khokar et al, 2015) are commonly used on humanoid robots.…”

Section: Humanoid Robot's Processing Unitsmentioning

confidence: 99%

A comprehensive survey on humanoid robot development

Saeedvand¹,

Jafari²,

Aghdasi³

et al. 2019

The Knowledge Engineering Review

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The development of a versatile, fully-capable humanoid robot as envisioned in science fiction books is one of the most challenging but interesting issues in the robotic field. Currently, existing humanoid robots are designed with different purposes and applications in mind. In humanoid robot development process, each robot is designed with various characteristics, abilities, and equipment, which influence the general structure, cost, and difficulty of development. Even though humanoid robot development is very popular, a few review papers are focusing on the design and development process of humanoid robots. Motivated by this, we present this review paper to show variations in the requirements, design, and development process and also propose a taxonomy of existing humanoid robots. It aims at demonstrating a general perspective of existing humanoid robots’ characteristics and applications. This paper includes state-of-the-art and successfully reported existing humanoid robot designs along with different robots used in various robot competitions.

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Section: Humanoid Robot's Processing Unitsmentioning

confidence: 99%

A comprehensive survey on humanoid robot development

Saeedvand¹,

Jafari²,

Aghdasi³

et al. 2019

The Knowledge Engineering Review

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“…Since Darwin's humanoid robot has no prismatic joint, therefore and the existing variables are . Using this translation matrix one can project the attached frames to anywhere in the robot kinematic chain on an arbitrary or reference frame [7].…”

Section: A Denavit-hartenberg Parameters Of the Robot Headmentioning

confidence: 99%

“…There are several solutions for inverse kinematics problem and the plurality of degrees of freedom exceeds these solutions [5]. To calculate the inverse kinematics of the robot hand, algebraic methods and for calculation of inverse kinematics of the robot leg, due to the complexity of the calculations, the geometric method is used [7].…”

Section: Inverse Kinematicsmentioning

confidence: 99%

“…In the process of solving, first the desired position in the workspace of the robot's right leg is considered, and then by using the obtained equations in Equations 21 to 28, angles is derived. It should be noted that it is possible to obtain more than one value for some angles which is the most appropriate solution will be considered [7]. …”

Section: Robot's Right Leg Inverse Kinematicsmentioning

confidence: 99%

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Kinematic analysis of Darwin's humanoid robot

Hasanpour

Daemy

Aghazamani

et al. 2016

2016 4th International Conference on Control, Instrumentation, and Automation (ICCIA)

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“…The common planning algorithms work in the joint space, so they need an Inverse Kinematics (IK) solver to compute the target robot configuration. Kinematic and Dynamic Solver (KDL) [7] is the most used IK solver: it is based on Newton's method with some random jumps. However, careless use of any IK solver can produce unneeded robot reconfigurations.…”

Section: Introductionmentioning

confidence: 99%

Motion Planning and Reactive Control Algorithms for Object Manipulation in Uncertain Conditions

et al. 2018

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This work proposes the application of several smart strategies for object manipulation tasks. A real-time flexible motion planning method was developed to be adapted to typical in-store logistics scenarios. The solution combines and optimizes some state-of-the-art techniques to solve object recognition and localization problems with a new hybrid pipeline. The algorithm guarantees good robustness and accuracy for object detection through depth images. A standard planner plans collision-free trajectories throughout the whole task while a proposed reactive motion control is active. Distributed proximity sensors were adopted to locally modify the planned trajectory when unexpected or misplaced obstacles intervene in the scene. To implement a robust grasping phase, a novel slipping control algorithm was used. It dynamically computes the grasp force by adapting it to the actual object physical properties so as to prevent slipping. Experimental results carried out in a typical supermarket scenario demonstrate the effectiveness of the presented methods.

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Implementation of KDL Inverse Kinematics Routine on the Atlas Humanoid Robot

Cited by 17 publications

References 2 publications

A comprehensive survey on humanoid robot development

A comprehensive survey on humanoid robot development

Kinematic analysis of Darwin's humanoid robot

Motion Planning and Reactive Control Algorithms for Object Manipulation in Uncertain Conditions

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