Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Rolling Resistance: Problem Solving

Rolling Resistance: Problem Solving

Rolling resistance, also known as rolling friction, is the force that resists the motion of a rolling object, such as a wheel, tire, or ball, when it moves over a surface. It is caused by the deformation of the object and the surface in contact with each other, as well as other factors like internal friction, hysteresis, and energy losses within the materials. Rolling resistance opposes the object's motion, requiring additional energy to overcome it and maintain movement. In practical...

Rolling Resistance

Rolling Resistance

When a solid cylinder rolls steadily on a rigid surface, the normal force applied by the surface on the cylinder is perpendicular to the tangent at the contact point. However, since no materials are entirely rigid, the surface's reaction to the cylinder involves a range of normal pressures.
For instance, imagine a hard cylinder rolling on a comparatively soft surface. The cylinder's weight compresses the surface beneath it. As the cylinder moves, the material in front of it slows down...

Relative Motion Analysis using Rotating Axes-Problem Solving

Relative Motion Analysis using Rotating Axes-Problem Solving

Consider a crane whose telescopic boom rotates with an angular velocity of 0.04 rad/s and angular acceleration of 0.02 rad/s2. Along with the rotation, the boom also extends linearly with a uniform speed of 5 m/s. The extension of the boom is measured at point D, which is measured with respect to the fixed point C on the other end of the boom. For the given instant, the distance between points C and D is 60 meters.
Here, in order to determine the magnitude of velocity and acceleration for point...

You might also read

Related Articles

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

Sort by

Same author

Peanut Shaped Microrobots for Anticancer Therapy.

... International Conference on Manipulation Automation and Robotics at Small Scales (MARSS). International Conference on Manipulation Automation and Robotics at Small Scales·2026

Same author

Engineering drug-responsive replication machinery for precise control of self-amplifying RNA.

Nature biomedical engineering·2026

Same author

Bio-inspired biped microwalker with magneto-acoustic actuation for cell manipulation.

Cell reports. Physical science·2026

Same author

Design and Control of a Novel Corkscrew Clawbot for Cell Manipulation.

... International Conference on Manipulation Automation and Robotics at Small Scales (MARSS). International Conference on Manipulation Automation and Robotics at Small Scales·2026

Same author

Automated control of catalytic Janus micromotors.

MRS advances·2026

Same author

Patchy Bubble-Propelled Colloids at Interfaces.

Advanced materials interfaces·2026

Same journal

Using Robotics to Improve Transcatheter Edge-to-Edge Repair of the Mitral Valve.

IEEE robotics and automation letters·2026

Same journal

Value Explicit Pretraining for Learning Transferable Representations.

IEEE robotics and automation letters·2026

Same journal

Continuum Robot Segments with High Output Stiffness via Diagonal Backbones.

IEEE robotics and automation letters·2026

Same journal

Friction Modeling of Tendon-driven Continuum Robots through Linear Complementarity Problem.

IEEE robotics and automation letters·2026

Same journal

Efficient and Scalable Tuning of Continuous Impedance Control for Powered Knee Prostheses.

IEEE robotics and automation letters·2026

Same journal

Validation of Dynamic Bayesian Optimization for a Non-Stationary Human-in-the-Loop Optimization Problem.

IEEE robotics and automation letters·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jun 17, 2025

Insect-controlled Robot: A Mobile Robot Platform to Evaluate the Odor-tracking Capability of an Insect

Insect-controlled Robot: A Mobile Robot Platform to Evaluate the Odor-tracking Capability of an Insect

Published on: December 19, 2016

Learning a Tracking Controller for Rolling μbots.

Logan E Beaver¹, Max Sokolich², Suhail Alsalehi¹

¹Division of Systems Engineering, Boston University, Boston, MA 02215, USA.

IEEE Robotics and Automation Letters

|August 12, 2024

Summary

This summary is machine-generated.

This study introduces a new control method for micron-scale robots (μbots) to improve trajectory tracking accuracy. The approach uses machine learning to compensate for environmental disturbances and model uncertainties, enhancing μbot navigation in medical applications.

Keywords:

Machine Learning for Robot Control Micro/Nano Robots Optimal Control Optimization

More Related Videos

Investigating Motor Skill Learning Processes with a Robotic Manipulandum

Investigating Motor Skill Learning Processes with a Robotic Manipulandum

Published on: February 12, 2017

An Innovative Running Wheel-based Mechanism for Improved Rat Training Performance

An Innovative Running Wheel-based Mechanism for Improved Rat Training Performance

Published on: September 19, 2016

Related Experiment Videos

Last Updated: Jun 17, 2025

Insect-controlled Robot: A Mobile Robot Platform to Evaluate the Odor-tracking Capability of an Insect

Insect-controlled Robot: A Mobile Robot Platform to Evaluate the Odor-tracking Capability of an Insect

Published on: December 19, 2016

Investigating Motor Skill Learning Processes with a Robotic Manipulandum

Investigating Motor Skill Learning Processes with a Robotic Manipulandum

Published on: February 12, 2017

An Innovative Running Wheel-based Mechanism for Improved Rat Training Performance

An Innovative Running Wheel-based Mechanism for Improved Rat Training Performance

Published on: September 19, 2016

Area of Science:

Robotics
Control Systems
Biomedical Engineering

Background:

Micron-scale robots (μbots) show potential for medical applications.
Accurate control of μbots is essential but challenging due to environmental disturbances and model uncertainties.

Purpose of the Study:

To develop a robust control strategy for μbots to accurately track reference trajectories.
To compensate for disturbances like Brownian motion and model parameter uncertainties.

Main Methods:

Modeled the μbot as an uncertain unicycle controlled by a magnetic field.
Developed a nonlinear mismatch controller to address disturbances and uncertainties.
Employed Gaussian Processes to learn model mismatch error and least-squares minimization for control action selection.

Main Results:

The joint learning and control algorithm demonstrated accurate online learning of model mismatch in simulations.
Improved trajectory tracking performance was observed in simulations.
Experimental validation showed a reduction in certain error metrics by up to 40%.

Conclusions:

The proposed nonlinear mismatch controller effectively compensates for μbot model uncertainties and environmental disturbances.
The integration of Gaussian Processes and least-squares minimization enhances μbot navigation accuracy.
This approach offers a promising solution for precise μbot control in medical applications.