Dorian Verdel

This study demonstrates that humans can effectively collaborate with autonomous wearable robotic limbs during dynamic tasks without visual feedback, achieving reliable task completion and high perceived safety.

This study decodes human intent during collaborative object manipulation using multimodal signals and explains how sensorimotor communication occurs through action.

The paper develops a computational model of active vision that explains how eye-hand coordination adapts to information context, showing how saccade-pursuit patterns emerge from minimizing task-related uncertainty.

This study shows how individual vigor affects dyadic coordination in physical tasks, with slower partners influencing dyadic vigor and coordination patterns.

This paper develops a model-predictive game controller for contact robots to improve human-robot interaction by predicting human control and adapting to individual motor strategies.

This paper introduces a framework for calibrating and evaluating EMG-to-torque models, including a novel nonlinear model that improves accuracy while maintaining computational efficiency.

This paper introduces an EMG-based controller for robotic exoskeletons that intentionally leaves gravity torque uncompensated, improving muscle effort reduction and kinematic performance in arm movements.

This study uses an exoskeleton as biofeedback to guide participants toward ergonomic postures by inducing vibrations that encourage adaptation to reduce effort.

This study introduces an information-based control framework that generates human-like movement behavior in discrete and continuous tasks by dynamically adjusting planning based on surprise and task constraints.

The paper shows that muscle co-contraction increases with environmental uncertainty to stabilize motor control when feedback is insufficient.

This study investigates how time and effort tradeoff influences human movement vigor when interacting with a robotic exoskeleton, finding that time cost plays a pivotal role in determining movement vigor across a range of efforts.

The paper shows humans can quickly adapt motor patterns to different gravity conditions using a robotic exoskeleton.