Skip to main content

Lego Mindstorms – Sentry Robots

Sameer Kumar Shrestha, Northampton

The report presents the dissertation on title Prototype of Sentry Robots for Advanced Security which includes the use of LEGO robots showing interaction between each other with the help of wireless communication medium in Bluetooth. The purpose of the work is to build a communication between multiple LEGO robots using the wireless technology. For this task, the NXT version of LEGO Mindstorms has been selected. It is because there is need of complex communication which is possible through wireless medium such as Bluetooth and also a suitable processing device for the proposed task which is present in the LEGO Mindstorms NXT. The report has also focused on the background information about the NXT system and its great flexibility with LeJOS NXJ as the programming platform. The outcome is the implementation of developed work with the use LEGO Mindstorms NXT and the LeJOS NXJ as programming platform. The task was approached with one LEGO NXT robot maintaining the distance between the object in the environment and searching the object by rotating in case of lost. After the completion of the first task, the next task was to study the communication behavior of multiple robots communicating with each other to fulfill the same job. For this, three NXT robots were taken and programmed in such a way that they form the shape of triangle and keep tracking the object.  All three of them send and wait for the information from each other and process this information to produce a suitable output, i.e. to respond to the action from each other. Thus, it was found that the implementation of several processes to multiple LEGO based communication had faults, due to the technical hitches with the communication technology and limitations of the NXT systems.

All opinions in this blog are the Author's and should not in any way be seen as reflecting the views of any organisation the Author has any association with.

Popular posts from this blog

Micro:bit, Servo control with Micropython or blocks

You can control servos (small ones) from a Micro:Bit directly. Following a link from the David Whale (Twitter ) , thank you, took me to a Kitronik blog post,, which has the answer.

The code uses Microsoft Blocks taken from the post, runs the servos 180 degrees and back again, when button A is pressed. It does exactly what it should. I am also using the Tower Pro SG90 servo.
Can it be replicated in Micropython? This is a new mini project, there seems to be little out there yet on how do this but the best so far is this video by PHILG2864:

The closest I have is the following, it is essentially there.
from microbit import *
while True:

Setting the time period to 20ms  pin0.set_analog_period(20)seems by experiment (and used in the video above) to be best value so far. The reason for pin0.write_analog(1)  set to 1 i…

mbots - graphical programming and Arduino

Makeblock ( funded through Kickstarter the development of a new robot - mBot ( with the subtitle "$49 educational robot for each kid". What they came up with is a interesting system that uses their mBlock software, which resembles Scratch but produces code for Arduino, to program a robot with LEDs, light sensors and buzzer integrated on the main board; but also comes with sensors for line-following, ultrasonic sensor and with the version in the kickstarter reward a 16x8 LED matrix.

My impression so far it is really quite intuitive to work with, in the example above the robot:

moves forward;displays 'f' on the LED matrix; turns right;displays 'r' on the LED matrix;repeats until the on-board is pressed to stop the motors. 

What I like most though is seeing the graphical code turned into Arduino code - the potential to see the same thing done into two ways…

4Tronix Bit:Bot Neuron Controlled Edge follower

In thelast post I was playing with 4Tronix'sBit:Bot. In this post I will show the initial experimentation with an artificial neuron controlling the Bit:Bot to follow the edge of a line (it follows the left-hand side of the line).

The neurons (well two separate ones, S1 and S2) are produced using weighted sums - summing the weights x inputs [ right-hand sensor (rs) and left-hand sensor (ls)] plus a bias for each neuron in this case w[0] and w[3].

    net=w[0]+w[1]*rs+w[2]*ls           net2=w[3]+w[4]*rs+w[5]*ls

  If weighted sum >=0 then its output 1 otherwise 0 if net>=0:          s1=1     else:         s1=0
    if net2>=0:         s2=1     else:         s2=0
What actual causes S1 to be either 1 or 0 is all defined by a set of weights w (three for the first neurone, S1,  three for S2).

Converting the outputs of the two neurones S1 and S2 into actions is shown below.