Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping

Area of Science:

• Robotics
• Human-Computer Interaction
• Motor Control
• Perception

Background:

• Successful object grasping requires identifying optimal hand contact regions.
• Estimating these contact regions is a significant challenge in robotics and human-computer interaction.
• Current methods lack precise identification of grasp points on real objects.

Purpose of the Study:

• To present a novel workflow for estimating hand-object contact regions using marker-based tracking data.
• To enable precise identification of grasp locations for real-world objects.
• To facilitate research in understanding human grasping and improving robotic manipulation.

Main Methods:

• Marker-based tracking of hand and object 3D positions, including finger joint data.
• Hand mesh reconstruction from tracked markers to create a dynamic hand model.
• Co-registration of reconstructed hand meshes with 3D object meshes (from 3D printing or scanning).
• Estimation of contact regions via mesh intersection calculations.

Main Results:

• A reproducible workflow for estimating grasp contact regions was established.
• The method successfully identified approximate contact areas between the hand and object meshes.
• Enabled co-registration of physical hand and object data with digital mesh models.

Conclusions:

• The described method provides a viable approach for estimating human grasp contact regions.
• This technique can be applied across various grasping conditions and object types.
• Findings are relevant for advancing research in haptic perception, motor control, VR/AR, and robotics.