Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Articulations of the Vertebral Column01:28

Articulations of the Vertebral Column

3.1K
In addition to being held together by the intervertebral discs, adjacent vertebrae also articulate with each other at synovial joints formed between the superior and inferior articular processes called zygapophysial joints (facet joints). These are plane joints that provide for only limited motions between the vertebrae. The orientation of the articular processes at these joints varies in different regions of the vertebral column and serves to determine the types of motions available in each...
3.1K
Muscles that Move the Arm01:31

Muscles that Move the Arm

4.8K
Nine muscles are involved in arm movements. Two of these, the pectoralis major and latissimus dorsi, originate from the axial skeleton and are called axial muscles. The other seven originate from the scapula and are called the scapular muscles.
The pectoralis major has two origins. Its clavicular head originates on the medial half of the clavicle. In contrast, the sternocostal head originates on the costal cartilages of ribs 1-6, the sternum, and the aponeurosis of the external oblique of the...
4.8K
Equation of Motion: General Plane motion01:22

Equation of Motion: General Plane motion

575
In the context of a rigid body's movement within a general plane, it is important to understand that this motion is typically triggered by external forces or couple moments exerted onto it. This principle can be explained through Newton's second law, which stipulates the translational motion of the body's center of mass along each axis.
Moreover, the body's center of mass experiences a rotational effect as a result of these couple moments. This rotation can be articulated as the...
575
Absolute Motion Analysis- General Plane Motion01:24

Absolute Motion Analysis- General Plane Motion

563
Visualize a drone, with its propellers spinning rapidly, hovering mid-air. The fascinating movements and operations of this drone can be comprehended by applying the principle of general plane motion.
As the drone's propellers rotate, an upward force is generated that counteracts the force of gravity, enabling the drone to lift off from the ground. This initial movement of the drone is along a straight path, representing a form of translational motion. In this phase, every point on the...
563
Equation of Motion: General Plane motion - Problem Solving01:16

Equation of Motion: General Plane motion - Problem Solving

505
Consider a lawn roller with a mass of 100 kg, a radius of 0.2 meters, and a radius of gyration of 0.15 meters. A force of 200 N is applied to this roller, angled at 60 degrees from the horizontal plane. What will be the angular acceleration of the lawn roller?
The friction between the roller and the ground is characterized by two coefficients. The static friction coefficient is 0.15, while the kinetic friction coefficient is 0.1. These values are crucial in understanding the interaction between...
505
Projectile Motion: Example01:18

Projectile Motion: Example

12.8K
The theory of projectile motion is very useful for players of several sports to improve their performance. For example, a javelin thrower needs to throw their javelin in such a way that it travels as far as possible. The javelin thrower takes a short run-up to increase the initial speed of the javelin. The range of a projectile is at its maximum at a 45° angle so javelin throwers try to angle their throw as close to 45° as possible.
When we speak of the range (R) of a projectile on...
12.8K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

The DSM-5 alternative model for personality disorders and psychotic symptoms: A two-sample study in help-seeking adolescents.

Schizophrenia research·2026
Same author

Integrating neurobiological markers to prospectively predict adolescent non-suicidal self-injury and suicide attempts: a machine learning approach.

Child and adolescent psychiatry and mental health·2026
Same author

Contextualizing the Future <i>DSM</i>: Cross-Cultural, Developmental, and Multi-Informant Considerations.

The American journal of psychiatry·2026
Same author

Experience with standardized assessments in child and adolescent psychiatry: Findings from a national trainee survey in Switzerland.

European child & adolescent psychiatry·2026
Same author

Understanding tonic and phasic irritability in developmental psychopathology among help-seeking children and adolescents in Switzerland: Protocol for the longitudinal multimodal UTOPICA study.

BMJ open·2026
Same author

Neurometabolic Stability and Heritability in the Adolescent Brain: A Preliminary Longitudinal Twin MRS Study.

NMR in biomedicine·2026

Related Experiment Video

Updated: Jan 30, 2026

Robotic Mirror Therapy System for Functional Recovery of Hemiplegic Arms
10:32

Robotic Mirror Therapy System for Functional Recovery of Hemiplegic Arms

Published on: August 15, 2016

16.0K

Articulated Robot Motion for Simultaneous Localization and Mapping (ARM-SLAM).

Matthew Klingensmith1, Siddartha S Sirinivasa1, Michael Kaess1

  • 1Carnegie Mellon Robotics Institute, 5000 Forbes Avenue, Pittsburgh PA 15213.

IEEE Robotics and Automation Letters
|January 15, 2019
PubMed
Summary

This study introduces a novel robot navigation method that simultaneously estimates joint angles and reconstructs 3D scenes. This approach improves 3D reconstruction and joint angle accuracy, enhancing robot perception in uncertain environments.

More Related Videos

Investigating Pain-Related Avoidance Behavior using a Robotic Arm-Reaching Paradigm
09:00

Investigating Pain-Related Avoidance Behavior using a Robotic Arm-Reaching Paradigm

Published on: October 3, 2020

4.5K
Non-Invasive Modulation and Robotic Mapping of Motor Cortex in the Developing Brain
08:26

Non-Invasive Modulation and Robotic Mapping of Motor Cortex in the Developing Brain

Published on: July 1, 2019

7.1K

Related Experiment Videos

Last Updated: Jan 30, 2026

Robotic Mirror Therapy System for Functional Recovery of Hemiplegic Arms
10:32

Robotic Mirror Therapy System for Functional Recovery of Hemiplegic Arms

Published on: August 15, 2016

16.0K
Investigating Pain-Related Avoidance Behavior using a Robotic Arm-Reaching Paradigm
09:00

Investigating Pain-Related Avoidance Behavior using a Robotic Arm-Reaching Paradigm

Published on: October 3, 2020

4.5K
Non-Invasive Modulation and Robotic Mapping of Motor Cortex in the Developing Brain
08:26

Non-Invasive Modulation and Robotic Mapping of Motor Cortex in the Developing Brain

Published on: July 1, 2019

7.1K

Area of Science:

  • Robotics
  • Computer Vision
  • Artificial Intelligence

Background:

  • Accurate 3D scene reconstruction is crucial for robot navigation.
  • Uncertainty in robot joint angles complicates simultaneous localization and mapping (SLAM).
  • Existing methods often rely on camera pose, neglecting robot kinematics.

Purpose of the Study:

  • To develop a method for simultaneous estimation of robot joint angles and 3D scene reconstruction.
  • To perform SLAM in the robot's configuration space, not camera pose space.
  • To improve the robustness and accuracy of 3D reconstruction despite uncertain sensor data.

Main Methods:

  • Simultaneous estimation of robot joint angles and dense volumetric scene reconstruction.
  • SLAM performed in the robot's configuration space.
  • Utilizing robot joint angles to constrain sensor pose.

Main Results:

  • Significant reduction in 3D reconstruction error compared to using only forward kinematics.
  • Substantial decrease in joint angle error.
  • Demonstrated robustness to missing or ambiguous depth data.

Conclusions:

  • The proposed method offers superior accuracy and robustness for robot 3D scene reconstruction.
  • Directly reasoning about robot joint angles provides a significant advantage over camera-centric approaches.
  • This approach enhances robot perception and navigation capabilities in complex environments.