36 citations · 54 across the 5 of their papers we have counts for
4 papers · 1 filter
Deep Reinforcement Learning with Population-Coded Spiking Neural Network for Continuous Control
Guangzhi Tang, Neelesh Kumar, Raymond Yoo +1
The energy-efficient control of mobile robots is crucial as the complexity of their real-world applications increasingly involves high-dimensional observation and action spaces, wh…
Reinforcement co-Learning of Deep and Spiking Neural Networks for Energy-Efficient Mapless Navigation with Neuromorphic Hardware
Guangzhi Tang, Neelesh Kumar, Konstantinos P. Michmizos
Energy-efficient mapless navigation is crucial for mobile robots as they explore unknown environments with limited on-board resources. Although the recent deep reinforcement learni…
Machine Learning for Motor Learning: EEG-based Continuous Assessment of Cognitive Engagement for Adaptive Rehabilitation Robots
Neelesh Kumar, Konstantinos P. Michmizos
Although cognitive engagement (CE) is crucial for motor learning, it remains underutilized in rehabilitation robots, partly because its assessment currently relies on subjective an…
Deep Learning of Movement Intent and Reaction Time for EEG-informed Adaptation of Rehabilitation Robots
Neelesh Kumar, Konstantinos P. Michmizos
Mounting evidence suggests that adaptation is a crucial mechanism for rehabilitation robots in promoting motor learning. Yet, it is commonly based on robot-derived movement kinemat…