Neural control of rhythmic arm movements.
In this paper we present an approach to robot arm control based on exploiting the dynamical properties of a simple neural network oscillator circuit coupled to the joints of an arm. The entrainment and input/output properties of the oscillators are used to perform a variety of tasks with the same architecture, without any modeling of the arm or its environment. The approach is implemented on two real robot arms, and has been used to tune into the resonant frequency of pendulums, perform multi-joint coordinated motion by turning cranks, and exploit the dynamics of a 'Slinky' toy to coordinate the motion of two arms. By exploiting the coupling between the physical arm and the neural oscillator, a range of complex behaviors can be achieved with a very simple system.
Williamson
Matthew M.
MM
MIT AI Laboratory, 545 Technology Square, Room 937, Cambridge, USA