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Related Concept Videos

Rolling Without Slipping01:09

Rolling Without Slipping

People have observed the rolling motion without slipping ever since the invention of the wheel. For example, one can look at the interaction between a car's tires and the surface of the road. If the driver presses the accelerator to the floor so that the tires spin without the car moving forward, there must be kinetic friction between the wheels and the road's surface. If the driver slowly presses the accelerator, causing the car to move forward, the tires roll without slipping. It is essential...
Rolling With Slipping01:14

Rolling With Slipping

Rolling with slipping is a physical phenomenon that occurs when a rolling object experiences both rotational and linear motion but also experiences frictional forces that cause slipping. This phenomenon can occur in various situations, such as when a tire rolls on a wet road or a ball rolls on a rough surface.
An object's rolling motion is characterized by its rotation around its axis, while linear motion refers to the object's translational motion along a surface. Frictional forces can affect...
Equation of Motion: General Plane motion - Problem Solving01:16

Equation of Motion: General Plane motion - Problem Solving

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...
Rolling Resistance: Problem Solving01:17

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...
Rotational Motion about a Fixed Axis01:26

Rotational Motion about a Fixed Axis

A rigid body's rotation around a fixed axis makes every point within it trace a circular path around a specific line or point. The term given to this type of spinning is defined by the angular position, symbolized by the angle θ. This angle is gauged from a static reference line to the revolving object. From this angular position, any variation is referred to as angular displacement, denoted by dθ. The extent of this displacement can be calculated in degrees, radians, or revolutions, where one...
Relative Motion Analysis - Acceleration01:10

Relative Motion Analysis - Acceleration

A slider-crank mechanism converts rotational motion from the crank into linear motion of the slider or vice versa. This mechanism consists of three main parts: the crank, the connecting rod, and the slider. The movement of the slider-crank is an example of general plane motion as the fluctuating angle between the crank and the connecting rod. Consider a segment AB where point A is at the end of the slider and point B is on the diametrically opposite end to point A, on a crack. The variance in...

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Related Experiment Video

Updated: Jul 16, 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

ROIV-SLAM: Rotation-Optimized Inertial-Visual SLAM for a Non-Coaxial Two-Wheeled Robot Under Roll Disturbances.

Chong Feng1, Cheng Ren1, Wenbo Gao1

  • 1College of Information and Communication, Dalian Minzu University, Dalian 116600, China.

Sensors (Basel, Switzerland)
|July 15, 2026
PubMed
Summary

This study introduces a Rotation-Optimized Inertial-Visual SLAM (ROIV-SLAM) system to improve state estimation for two-wheeled robots. ROIV-SLAM enhances trajectory consistency and mapping robustness by decoupling motion estimation and incorporating physical constraints.

Keywords:
SLAMmotion disturbancesnon-coaxial two-wheeled robotrotation optimizationvisual–inertial fusion

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Using Eye-tracking to Assess the Relative Importance of Visual and Vestibular Input to Subcortical Motion Processing in the Roll Plane
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Using Eye-tracking to Assess the Relative Importance of Visual and Vestibular Input to Subcortical Motion Processing in the Roll Plane

Published on: August 22, 2025

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Last Updated: Jul 16, 2026

Robotic Mirror Therapy System for Functional Recovery of Hemiplegic Arms
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Robotic Mirror Therapy System for Functional Recovery of Hemiplegic Arms

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Using Eye-tracking to Assess the Relative Importance of Visual and Vestibular Input to Subcortical Motion Processing in the Roll Plane
07:24

Using Eye-tracking to Assess the Relative Importance of Visual and Vestibular Input to Subcortical Motion Processing in the Roll Plane

Published on: August 22, 2025

Area of Science:

  • Robotics
  • Computer Vision
  • Simultaneous Localization and Mapping (SLAM)

Background:

  • Two-wheeled robots face challenges with high-frequency roll disturbances during dynamic balancing.
  • Robust state estimation is crucial for navigation and control in these systems.

Purpose of the Study:

  • To propose a novel Rotation-Optimized Inertial-Visual SLAM (ROIV-SLAM) system.
  • To enhance state estimation robustness for non-coaxial two-wheeled robots experiencing dynamic balancing disturbances.

Main Methods:

  • A decoupled architecture for translation and rotation estimation.
  • Front-end: Extended Kalman Filter (EKF) fusing LiDAR, IMU, and wheel odometry for translation.
  • Back-end: Lie-group optimization with physical manifold constraints for rotation, enhanced loop closure via vision-LiDAR scan matching.

Main Results:

  • ROIV-SLAM demonstrated improved trajectory consistency against optimized reference trajectories.
  • Achieved more robust mapping performance compared to baseline approaches.
  • Successfully suppressed high-frequency motion noise inherent to balancing robots.

Conclusions:

  • The decoupled estimation mechanism and task-specific physical dynamic constraints are key to improving robustness.
  • ROIV-SLAM offers a viable solution for reliable state estimation in complex environments for balancing robots.