## 4 Results  
The SNN has been coded in PyNN and downloaded to SpiNNaker. After the network was downloaded, the SpiNNaker board (i.e., the ethernet link) has been disconnected from the laptop, to demonstrate PC-independent operation. Once the simulation starts, the SNN will run for arbitrary time (typically 60 s in our experiments) with a time step of 1 millisecond. The input layer receives the injected spikes from the microcontroller, and the output layer has eight neurons corresponding to the eight positions. The network will not send any packets unless a neuron in the output population is spiking. A demo video of the robot goalie action can be found at the following link: [[https://www.youtube.com/watch?v=135](https://www.youtube.com/watch?v=135) fH21 QXtg]([https://www.youtube.com/watch?v=135](https://www.youtube.com/watch?v=135) fH21 QXtg). The neuromorphic goalkeeper achieves an accuracy of up to 85% on the condition that the speed of the ball is up to 1 m/s and the initial distance more than 80 cm. For the hardware communication, the logical levels of the ACK signals of injecting spikes (uplink) and receiving spikes (downlink) are monitored to measure the transmission speed, Figure 9. As can be observed both ACK signals of uplink and downlink have changed 11 times to send a packet, which indicates that data is in the form of 40-bit packets followed by an EOP symbol. According to the reading of the oscilloscope, the frequencies of uplink and downlink ACK signals are 16.951 kHz and 16.970 kHz, respectively. Two symbols are sent in one period, since the logical levels of ACK signals change twice every period. Therefore, the uplink speed is:  
\[V_{uplink}=16.951\;\mathrm{kHz}\times 2=33.902\;\mathrm{Ksymbol}/\mathrm{s} \cong 3082\;\mathrm{packets}/\mathrm{s}\]  
The download speed is:  
\[V_{downlink}=16.970\;\mathrm{kHz}\times 2=33.940\;\mathrm{Ksymbol}/\mathrm{s} \cong 3085\;\mathrm{packets}/\mathrm{s}\]  
The microcontroller receives events in parallel but injects and receives spikes in serial. Thus, the speed of receiving events is higher than the speed of injecting and receiving spikes. Figure 8: Workflow of the robotic system used for interception of a moving object. Figure 9: The logical levels of the acknowledge (ACK) signals (Yellow: downlink, Blue: uplink) during transmission at the maximum speed. Since each process are parallelly executed and the speed of injecting spikes is higher than the speed of receiving spikes, the response latency is dominated by the time cost to inject spikes. Furthermore, the servo command is generated based on 20 spikes. Thus, the response latency is:  
\[t_{latency}=20\times\frac{1}{3082}\;\mathrm{s}\cong 6.489\;\mathrm{ms}\]  
The SNN was running for 1 min in multiple trials, and its output spikes were recorded. Since the servo motor was set to have eight movable positions, the abscissa of the coordinate where the ball can move is also divided equally into eight parts. The microcontroller obtains current coordinate of the moving ball from DVS and inputs it to the SNN. The classification of the coordinate will then be output by the SNN. For example, neuron 6 in the output layer of the SNN will spike if current abscissa of the moving ball is in the 6 th position. An example of the SNN activity for some randomly released balls is shown in Figure 10. The output spikes are concentrated at one or two neuron IDs in a short period, which gives strong and effective guidance for the microcontroller to generate servo commands. Because of the voting method applied in Figure 4, the effect of random noise has been reduced. The neuromorphic robotic system has a maximum power consumption of 7.15 W, which is calculated in the following way. For DVS at high activity, its supply voltage is 5 V and the current is 100 mA. For the microcontroller, its operational voltage is 3.3 V and it has a maximum fuse current of 500 mA. For SpiNN-3 board, its power supply is 5 V, idle current is 400 mA and peak current is 1 A [31].