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The SpiNNaker Hardware platform allows emulating generic neural network topologies, where each neuron-to-neuron connection is defined by an independent synaptic weight. Consequently, weight storage requires an important amount of memory in the case of generic neural network topologies. This is solved in SpiNNaker by encapsulating with each SpiNNaker chip (which includes 18 ARM cores) a 128MB DRAM...
Artificial neural networks increasingly involve spiking dynamics to permit greater computational efficiency. This becomes especially attractive for on-chip implementation using dedicated neuromorphic hardware. However, both spiking neural networks and neuromorphic hardware have historically found difficulties in implementing efficient, effective learning rules. The best-known spiking neural network...
In todays aging society, many people require mobility assistance, that can be provided by robotized assistive wheelchairs with a certain degree of autonomy when manual control is unfeasible due to disability. Robot wheelchairs, though, are not supposed to be completely in control because lack of human intervention may lead to loss of residual capabilities and frustration. Most of these systems rely...
This paper presents an efficient approach for implementing spike-timing-dependent plasticity (STDP) on the SpiNNaker neuromorphic hardware. The event-address mapping and the distributed synaptic weight storage schemes used in parallel neuromorphic hardware such as SpiNNaker make the conventional pre-post-sensitive scheme of STDP implementation inefficient, since STDP is triggered when either a pre-...
Large-scale neural hardware systems are trending increasingly towards the “neuromimetic” architecture: a general-purpose platform that specialises the hardware for neural networks but allows flexibility in model choice. Since the model is not hard-wired into the chip, exploration of different neural and synaptic models is not merely possible but provides a rich field for research: the possibility...
This paper presents a study on human performance when people are assisted by a purely reactive navigation control system. The goal of such a system is to achieve collaborative human/robot navigation, so that the human driver is always in control but his/her performance is improved by the machine. This Shared Control approach is meant to be implemented on a power robotic wheelchair, so it is important...
Autonomous robots are capable of navigating on their own. In some cases, though, it is interesting to allow humans to influence navigation. Shared control is typically achieved either by giving control to the human or the robot at some specific situations. In this work, we propose a method to share control between humans and robots at each point of a given trajectory, so that both have weight in the...
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