TY  - JOUR
AB  - A neural network controller is proposed for the motion control of robot manipulators with force/torque feedback signals. This controller is trained with reinforcement learning algorithms and a model is extracted from the synaptic weights within the neural network. This model is continuously refined by the feedback signals to ensure its validity even in a stochastic and non‐stationary environment. With this model and the real‐time force/torque feedback data, the robot can acquire a fine skill for a particular assembly task for which it is trained.
VL  - 21
IS  - 2
SN  - 0144-5154
DO  - 10.1108/01445150110388522
UR  - https://doi.org/10.1108/01445150110388522
AU  - Lau H.Y.K.
AU  - Lee I.S.K.
PY  - 2001
Y1  - 2001/01/01
TI  - Assembly skill acquisition via reinforcement learning
T2  - Assembly Automation
PB  - MCB UP Ltd
SP  - 136
EP  - 142
Y2  - 2024/04/26
ER  -