Task 3: Treasure hunt



16TH OCTOBER, 2012

Our Experience

The task was interesting because of its seeming complexity and thought required to accomplish it. Initially it sounded very abstract and almost impossible to perfectly program but as we reasoned through it logically, we were able to break it down into very basic tasks. These included object detection using the sonar, wall following, collision prevention as well as grabbing and dropping the bottle. We began by designing small modules to accomplish specific tasks and testing them individually before gradually putting them together into a complete program.We modified the program continually and even redesigned the robot a number of times as we researched and found new insight.

Lessons learnt

The main lessons we learnt from this task were how to use the compass sensor, sensor fusion (in our case, using the sonar with the color sensor for object detection) and ways of reducing sensor noise. We also gained a better understanding on how to manage separate tasks using the signals from the sensors.

Challenges faced

The first challenge we faced was getting all the required sensors to work together. We noticed that on several occasions we had different sensors causing the robot to perform conflicting actions and in effect producing very awkward results. Also, we were not able to make good use of the multiplexer due to its complexity even though it would have been helpful at some point. This caused a change in our design. In the end, we stuck to using four sensors and managed to have them coordinate to produce similar results as would have been possible with a few more sensors.

Another challenge worth mentioning was the difficulty in planning a reliable motion path for the robot in order to accomplish its task. For the greater part of the task, we stuck with using random motion which was unreliable and greatly increased the time it took to accomplish the task.

Problem Solving with sensors

  1. Fixing Potholes:

Many roads in Ghana are covered with potholes and other forms of damages which often cause deadly accidents especially in the rainy season. An important aspect of solving this problem is data collection. Data collected about the current condition of the road will help make estimates for either considering repairs or a complete reconstruction as well as providing useful information to road users on avoiding certain sections of roads.

Measuring every hole and crack on the road manually would cost a lot of money and time. With the help of sensor and additional image recognition software, we could create a system which recognizes the damages on a road and estimates the cost of fixing it. Sensors which can be used may include a camera to capture images to be analysed and an accelerometer to collect data about how bumpy the road is. These sensors may be simple accelerometers and cameras available on phones or could come as part of more advanced equipment. Over time, as more roads are traversed a very reliable database could be established with enough information to help with more efficient means of repairing damaged roads.

  1. Flood Prevention:

Many communities in Ghana suffer from floods every year. Floods are usually caused by the overflow of rivers during the rainy season and often cause massive loss of property and sometimes loss of lives. Because of the lack of alarm mechanisms, affected communities don’t normally have enough time to prepare to leave or move their properties.

A mechanism which could help to reduce the loss in life and property could be built using sensors which could measure change in water levels in rivers. The level of water in the river could be measured using a level sensor. Some level sensors which can be used for this purpose may include ultrasonic level sensors, capacitive sensor, and mechanical diaphragm. With these sensors being constantly monitored, meteorological agencies and disaster prevention organisations would have enough time to warn communities and also be well prepared to deal with floods if they could not be prevented.


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