Gradient boosting machines are a family of powerful machine-learning techniques that have
shown considerable success in a wide range of practical applications. They are highly …

In this paper, an improved recurrent neural network (RNN) scheme is proposed to perform
the trajectory control of redundant robot manipulators using remote center of motion (RCM) …

Decoding the human brain is perhaps the most fascinating scientific challenge in the 21st
century. The Human Brain Project (HBP), a 10-year European Flagship, targets the …

Tying suture knots is a time-consuming task performed frequently during minimally invasive
surgery (MIS). Automating this task could greatly reduce total surgery time for patients. …

In many future joint-action scenarios, humans and robots will have to interact physically in
order to successfully cooperate. Ideally, seamless human-robot interaction should not require …

Reinforcement learning (RL) has achieved tremendous success in many complex decision
making tasks. When it comes to deploying RL in the real world, safety concerns are usually …

As a bio-inspired and emerging sensor, an event-based neuromorphic vision sensor has a
different working principle compared to the standard frame-based cameras, which leads to …

Biologically inspired spiking neural networks are increasingly popular in the field of artificial
intelligence due to their ability to solve complex problems while being power efficient. They …

The Human Brain Project (HBP) is a candidate project in the European Union's FET Flagship
Program, funded by the ICT Program in the Seventh Framework Program. The project will …

Pedestrian motion prediction is a fundamental task for autonomous robots and vehicles to
operate safely. In recent years many complex approaches based on neural networks have …