Overview of the Intelligent Systems (IS) Focus at Clemson Tim Burg Department of Electrical and Computer Engineering Clemson University

Defining an Intelligent System Sensing Vision Estimation Controller Computing Control Algorithm Linear Nonlinear System Electrical Biological Chemical Mechanical Robotic Output

Core Expertise in Intelligent Systems Tim Burg Haptics Biofabrication Stan Birchfield Vision Processing Darren Dawson Nonlinear Control Richard Groff Magnetic Fiber Control Ian Walker Soft Robots Ian Walker Soft Robots

Interesting Haptic Result Dynamic touch - use of muscle sensitivity to perceive mechanical properties of objects that are wielded in space. Can lift a coffee cup by its handle to estimate the volume Attunement - user converges on perceptual variables that are correlated with the perceived property Calibration - learning of the correct scaling factor for specifying variables through feedback

Sense Mechanical Parameters When Wielding Human haptic system is sensitive to time-varying forces and torques, it seems to use them to register mechanical quantities that remain invariant. Subjects can estimate length

Tricking Perception of Mechanical Parameters Masses attached at various positions on each rod so as to break the natural covariation between moments, show that length perception is related to Inertia and Static Moment Subjects incorrectly estimate length

Haptic Device to Reproduce Experiments Can the device reproduce the dynamics of the wielded rod so user can estimate length? Can the device be used to attune the user to specific mechanical variables? Can the user be trained (calibrated) to estimate length from the perceived variables? Quansar 5DOF Haptic Wand

Experimental Design of Haptic Experiments Haptic Simulation

Results Results from the study suggest that subjects can be trained by the process of attunement and calibration to estimate physical properties (like length) based on perceived haptic information. The primary implications of these findings pertain to the design of virtual haptic surgical simulators where kinesthetic parameters may improve haptic perception and skills training and the transfer of learned skills to real environments. Conversely, if haptic feedback is not addressed in the simulator design then inappropriate, hidden negative training may occur that may be detrimental to skills transfer.

A More Theoretical Framework Modeling – Haptics as a Leader/Follower System Control Design to Make Leader “Feel” the Environment of the Follower Observer to Estimate Input Force

Where Can We Collaborate? Sensing Vision Estimation Controller Computing Control Algorithm Linear Nonlinear System Electrical Biological Chemical Mechanical Robotic Output Tim Burg (tburg@clemson.edu) Department of Electrical and Computer Engineering Clemson University