Remembering Motor Skills with Reward-Based Reinforcement, Haptic Guidance, and Error Augmentation

Submitted by Dylan Losey on Sat, 04/30/2016 - 14:10

There has been significant research aimed at leveraging programmable robotic devices to provide haptic assistance or augmentation to a human user so that new motor skills can be trained efficiently and retained long after training has concluded. The success of these approaches has been varied, and retention of skill is typically not significantly better for groups exposed to these controllers during training. These findings point to a need to incorporate a more complete understanding of human motor learning principles when designing haptic interactions with the trainee.

Project Status:

Inactive

O'Malley reunites with IEEE HAPTICS past chairs

Submitted by Marcia O'Malley on Wed, 04/13/2016 - 00:52

Colgate, Tan, Jones, Kuchenbecker, Basdogan, Choi, O'Malley, Gerling

Congratulations Dr. Pehlivan!

Submitted by Marcia O'Malley on Wed, 04/13/2016 - 00:41

Utku defended his PhD on 4/12/16

MAHI lab to host Edoardo Battaglia

Submitted by Marcia O'Malley on Wed, 04/13/2016 - 00:39

Visiting researcher won Best Paper at IEEE HAPTICS 2016

MAHI Reunion at Haptics Conference

Submitted by Marcia O'Malley on Mon, 04/11/2016 - 09:13

A Time Domain Approach to Control of Series Elastic Actuators: Adaptive Torque and Passivity-Based Impedance Control

Submitted by Dylan Losey on Thu, 03/31/2016 - 12:11

Robots are increasingly designed to physically interact with humans in unstructured environments, and as such must operate both accurately and safely. Leveraging compliant actuation, typically in the form of series elastic actuators (SEAs), can guarantee this required level of safety. To date, a number of frequency domain techniques have been proposed which yield effective SEA torque and impedance control; however, these methods are accompanied by undesirable stability constraints.