Manipulator Trajectory
Manipulator Trajectory - Related Videos
16:14
Trajectory Data Analyses for Pedestrian Space-time Activity Study
0 Views •
Cited by 15 •
2013
A suite of spatiotemporal processing methods are presented to analyze human trajectory data, such as that collected using a GPS device, for the purpose of modeling pedestrian space-time activities.
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Osteopathic Manipulative Treatment as a Useful Adjunctive Tool for Pneumonia
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Cited by 50 •
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Pneumonia is one of the top ten leading causes of death in the U.S. Osteopathic manipulative techniques (OMT) may be utilized as an adjunctive therapy in the treatment of pneumonia to enhance biomechanical and immune function; and ultimately, to reduce hospital stay, duration of antibiotics, incidence of respiratory failure, and mortality. In this video-article, we will review randomized controlled studies on the use of OMT in pneumonia patients, as well as demonstrate specific hands-on...
01:26
Orthogonal Trajectories
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2026
Orthogonal trajectories describe the geometric relationship between two families of curves that intersect each other at right angles. One illustrative case involves a family of parabolas that open sideways along the x-axis. These curves share a common shape but differ by a scaling parameter, resulting in a set of curves that all pass through the origin and widen at different rates.Determining Orthogonal TrajectoriesTo identify the orthogonal trajectories for these parabolas, the first step...
04:24
Studying Cell Rolling Trajectories on Asymmetric Receptor Patterns
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Cited by 3 •
2011
We describe a protocol to observe and analyze cell rolling trajectories on asymmetric receptor-patterned substrates. The resulting data are useful for engineering of receptor-patterned substrates for label-free cell separation and analysis.
11:00
Hand Controlled Manipulation of Single Molecules via a Scanning Probe Microscope with a 3D Virtual Reality Interface
0 Views •
Cited by 6 •
2016
We demonstrate the precise manipulation of individual organic molecules on a metal surface with the tip of a scanning probe microscope driven in 3D by the experimenter's hand using a motion capture system and fully immersive virtual reality goggles.
FAQs
Forward kinematics determines the end-effector position or pose from known joint values, while inverse kinematics finds joint values that achieve a specified end-effector state. Engineers use these complementary calculations to translate between task-space requirements and coordinated joint motion. Their results provide the basis for selecting feasible waypoints and generating movement that reaches the intended task states accurately.
Joint-space interpolation coordinates changes in individual joint variables, whereas Cartesian interpolation focuses on how the end effector moves through positions or poses. The choice depends on whether consistent joint coordination or task-space motion is more important. Comparing these approaches helps engineers produce motion that is smooth, accurate, and appropriate for operations such as assembly, machining, or welding.
Velocity and acceleration limits constrain how quickly joints and the end effector can move or change speed, while jerk limits control how abruptly acceleration changes. Applying these limits makes a planned motion more feasible and smooth. The resulting trajectory can reduce undesirable motion and support safer, more controlled operation when multiple joints move together.
Three important evaluation measures are tracking error, smoothness, and computational cost. Tracking error indicates how closely the robot follows the planned motion, while smoothness reflects the quality of changes in movement. Computational cost shows how demanding the planning method is. Considering all three helps engineers compare methods for precision, cycle time, and adaptability.
Engineers begin by specifying task positions or poses and identifying the states the robot must reach. They then apply forward or inverse kinematics, choose joint-space or Cartesian waypoints, and interpolate motion between those waypoints. Velocity, acceleration, and sometimes jerk limits are applied before evaluating tracking error, smoothness, and computational cost.
Planned motion supports accurate assembly, machining, welding, and material handling. In each case, coordinated joint movement helps the end effector reach required task states while limiting undesirable motion. Evaluating trajectory quality can guide improvements in precision, safety, cycle time, and adaptability, making trajectory planning relevant to both industrial robots and research platforms.