TPS-Motion-Model

Collect point cloud data from LiDAR sensors.

Extract features from the point cloud data using the point cloud feature extraction module.

Input the features into the transformer-based motion prediction model.

Obtain predicted trajectories for surrounding objects.

Use the predicted trajectories to plan a safe navigation path.

Collect point cloud data from depth cameras.

Segment the point cloud to isolate the object being manipulated.

Input the segmented point cloud into the motion prediction model.

Obtain predicted trajectories for the object.

Use the predicted trajectories to plan robot arm movements.

Collect point cloud data from motion capture sensors.

Input the point cloud data into the motion prediction model.

Obtain predicted trajectories for the user's movements.

Update the virtual environment based on the predicted trajectories.

Provide feedback to the user based on their interactions.

Acquire point cloud data via LiDAR or depth cameras.

Process and filter the data to identify individuals.

Input the point cloud data of identified individuals into the motion prediction model.

Generate predictive trajectories to forecast potential movement paths.

Alert security personnel if predicted trajectories deviate from normal patterns.

Capture human motion data via wearable sensors or depth cameras.

Input the captured data into the TPS-Motion-Model.

Generate predictive trajectories of human movements.

Adjust robot movements in real-time to avoid collisions and optimize task execution.

Monitor human-robot interaction and refine prediction models based on feedback.