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

Kinematic Equations: Problem Solving01:15

Kinematic Equations: Problem Solving

18.4K
When analyzing one-dimensional motion with constant acceleration, the problem-solving strategy involves identifying the known quantities and choosing the appropriate kinematic equations to solve for the unknowns. Either one or two kinematic equations are needed to solve for the unknowns, depending on the known and unknown quantities. Generally, the number of equations required is the same as the number of unknown quantities in the given example. Two-body pursuit problems always require two...
18.4K
One-Degree-of-Freedom System01:24

One-Degree-of-Freedom System

568
In mechanical engineering, one-degree-of-freedom systems form the basis of a wide range of electrical and mechanical components. Using these models, engineers can predict the behavior of various parts in a larger system, which gives them insight into how different forces interact with each other.
A one-degree-of-freedom system is defined by an independent variable that determines its state and behavior. One example of a one-degree-of-freedom system is a simple harmonic oscillator, such as a...
568
Kinematic Equations - II01:17

Kinematic Equations - II

11.4K
The second kinematic equation expresses the final position of an object in terms of its initial position, the distance traveled with the initial constant velocity, and the distance traveled due to a change in velocity. Similar to the first kinematic equation, this equation is also only valid when the acceleration is constant throughout the motion of an object.
Suppose a car merges into freeway traffic on a 200 m long ramp. If its initial velocity is 10 m/s and it accelerates at 2 m/s2, then the...
11.4K
Kinematic Equations for Rotation01:30

Kinematic Equations for Rotation

409
In mechanics, when one observes a rigid body in rotational motion with constant angular acceleration, it is possible to establish equations for its rotational kinematics. This process resembles how linear kinematics are dealt with in simpler motion studies.
For instance, imagine a point A on a rigid body engaged in circular motion. The translational velocity of this particular point can be calculated by taking the time derivatives of the displacement equation, which essentially measures the...
409
Kinematic Equations - III01:18

Kinematic Equations - III

9.1K
The first two kinematic equations have time as a variable, but the third kinematic equation is independent of time. This equation expresses final velocity as a function of the acceleration and distance over which it acts. The fourth kinematic equation does not have an acceleration term and provides the final position of the object at time t in terms of the initial and final velocities. This equation is useful when the value of the constant acceleration is unknown.
Using the kinematic equations,...
9.1K
Kinematic Equations - I01:26

Kinematic Equations - I

12.7K
When an object moves with constant acceleration, the velocity of the object changes at a constant rate throughout the motion. The kinematic equations of motions are derived for such cases where the acceleration of the object is constant. The first kinematic equation gives an insight into the relationship between velocity, acceleration, and time. We can see, for example:
12.7K

You might also read

Related Articles

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

Sort by
Same author

The Impact of Cardiac Magnetic Resonance Imaging on Revascularization in Ischemic Left Ventricular Dysfunction.

Life (Basel, Switzerland)·2026
Same author

Balancing Biomechanics and Preference in Assistive Device Tuning via Metric-Regularized Optimization.

IEEE transactions on bio-medical engineering·2026
Same author

Beyond Humanoid Prosthetic Hands: Modular Terminal Devices That Improve User Performance.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society·2025
Same author

Examining the physical and psychological effects of combining multimodal feedback with continuous control in prosthetic hands.

Scientific reports·2025
Same author

Quality assurance of late gadolinium enhancement cardiac magnetic resonance images: a deep learning classifier for confidence in the presence or absence of abnormality with potential to prompt real-time image optimization.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance·2024
Same author

Efficient labelling for efficient deep learning: the benefit of a multiple-image-ranking method to generate high volume training data applied to ventricular slice level classification in cardiac MRI.

Journal of medical artificial intelligence·2023

Related Experiment Video

Updated: Oct 3, 2025

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

15.6K

Kinematic-Model-Free Predictive Control for Robotic Manipulator Target Reaching With Obstacle Avoidance.

Ahmad AlAttar1,2, Digby Chappell1, Petar Kormushev1

  • 1Robot Intelligence Lab, Dyson School of Design Engineering, Imperial College London, London, United Kingdom.

Frontiers in Robotics and AI
|February 21, 2022
PubMed
Summary

This study introduces a novel kinematic-model-free predictive controller for robot manipulators. This innovative approach enables robots to reach targets and avoid obstacles without prior system modeling, even for complex robot types.

Keywords:
adaptive controlkinematic-model-freemodel-free controlobstacle avoidancepredictive controltarget reaching

More Related Videos

An Emerging Target Paradigm to Evoke Fast Visuomotor Responses on Human Upper Limb Muscles
09:27

An Emerging Target Paradigm to Evoke Fast Visuomotor Responses on Human Upper Limb Muscles

Published on: August 25, 2020

4.4K
Design and Implementation of a Bespoke Robotic Manipulator for Extra-corporeal Ultrasound
07:41

Design and Implementation of a Bespoke Robotic Manipulator for Extra-corporeal Ultrasound

Published on: January 7, 2019

9.3K

Related Experiment Videos

Last Updated: Oct 3, 2025

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

15.6K
An Emerging Target Paradigm to Evoke Fast Visuomotor Responses on Human Upper Limb Muscles
09:27

An Emerging Target Paradigm to Evoke Fast Visuomotor Responses on Human Upper Limb Muscles

Published on: August 25, 2020

4.4K
Design and Implementation of a Bespoke Robotic Manipulator for Extra-corporeal Ultrasound
07:41

Design and Implementation of a Bespoke Robotic Manipulator for Extra-corporeal Ultrasound

Published on: January 7, 2019

9.3K

Area of Science:

  • Robotics
  • Control Systems
  • Artificial Intelligence

Background:

  • Model predictive control (MPC) is standard for robot path planning but requires accurate system models.
  • Modeling challenges arise with complex robots (soft, continuum) and unknown environments.
  • Kinematic-model-free control offers a solution by learning models online.

Purpose of the Study:

  • To present a novel perception-based robot motion controller: the kinematic-model-free predictive controller.
  • To enable robot manipulator control without prior kinematic or dynamic parameter knowledge.
  • To achieve simultaneous target reaching and end-effector obstacle avoidance.

Main Methods:

  • Developed a kinematic-model-free predictive controller.
  • Employed online learning of local linear models.
  • Integrated perception for real-time environmental awareness.
  • Validated through simulations and physical experiments.

Main Results:

  • The controller successfully operated robot manipulators without prior system identification.
  • Simultaneous target reaching and obstacle avoidance were achieved.
  • Demonstrated adaptability in complex scenarios.

Conclusions:

  • The kinematic-model-free predictive controller is effective for robot manipulation in unknown environments.
  • This approach overcomes limitations of traditional model-based control for challenging robot morphologies.
  • The controller shows significant potential for real-world robotic applications requiring adaptability and autonomy.