Elias De Coninck — accepted AI-conference papers

2019

Learning to Grasp Arbitrary Household Objects from a Single Demonstration

Elias De Coninck, Tim Verbelen, Pieter Van Molle, Pieter Simoens, Bart Dhoedt IDLab

IROS 2019poster

Upon the advent of Industry 4.0, collaborative robotics and intelligent automation gain more and more traction for enterprises to improve their production processes. In order to adapt to this trend, new programming, learning and collaborative techniques are investigated. Program-bydemonstration is o…

Cited by 3 Source ↗Scholar ↗

2017

Sensor fusion for robot control through deep reinforcement learning

Steven Bohez, Tim Verbelen, Elias De Coninck, Bert Vankeirsbilck, Pieter Simoens, Bart Dhoedt

IROS 2017poster

Deep reinforcement learning is becoming increasingly popular for robot control algorithms, with the aim for a robot to self-learn useful feature representations from unstructured sensory input leading to the optimal actuation policy. In addition to sensors mounted on the robot, sensors might also be…

Cited by 44 Source ↗Scholar ↗