PhD Position Accounting for users’ diversity when designing robotic training methods

Updated: 14 days ago
Deadline: tomorrow

Robotic devices provide new possibilities for understanding and accelerating motor (re)learning. For example, robotic strategies that haptically reduce or augment/promote movement errors have been developed to enhance motor learning and neurorehabilitation. However, investigation of new haptic training methods yielded inconclusive results regarding their effectiveness to enhance motor learning, probably due to the different studied motor tasks, investigated haptic methods, and especially, the diversity in participants’ abilities and characteristics.

Within this project, you will study the role that participant’s characteristics (evaluated through qualitative and quantitative measurements, e.g., personality traits, sex, cultural background, attitude towards robots, etc) and task’s characteristics play on the effectiveness of haptic training methods. You will perform a systematic analysis of the relative benefits of novel robotic training strategies that assist/challenge the trainees based on trainees’ characteristics. You will then develop novel robotic training methods that adapt to account for trainee’s diversity to seamlessly interact with them in more naturalistic manners to enhance the training effectiveness in a way that trainees feel engaged and fulfilled.

Near-future robot intelligence offers great potential for our society, provided we can co-operate with this technology. The Human-Robot Interaction group is embedded in the Cognitive Robotics Department at TU Delft, where we aim to contribute to the responsible development of robotic technologies in human-inhabited environments. We do so by research organized in four groups: computer vision for intelligent vehicles, machine learning for learning and autonomous control, robot dynamics and human-robot interaction.

In the Human-Robot Interaction group we work on Motor Learning and Neurorehabilitation Robotics (the team headed by Laura Marchal-Crespo), Cognitive Human-Robot Interaction (the team headed by Joost de Winter), and on Physical Human-Robot Interaction (the Delft Haptics Lab, a team headed by David Abbink). Strong collaborations exist with cross-faculty institutes (TU Delft Robotics Institute and TU Delft Transport Institute), our national robotic ecosystem (RoboValley, Holland Robotics), Clinical partners (Erasmus MC), and international industry and academia.


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