Treasure Hunt Task

Task: Treasure Hunt

Group Members:

Flynn Darko

Daniel Botchway

Lecturer: Dr. Ayorkor Korsah

 

Task 3 Report

Introduction & Objective

Our main goal for this task was to write a program for the robot that would enable it find red and blue colored bottles and place them in their respective color zones (holding stations) with the help of sensors attached to the robot.

Design Concept

First, we had to rebuild our robot from task 2 to enable it grab and transport the bottles to the collection points. Treasures are shown in figure 1.

Bottles wrapped in colored cards

Bottles wrapped in colored cards (treasures)

 

  • For the robot and its sensors

For our robot we decided on the “Tribot” model of the robot. The sensors we decided to use were two sonar sensors and two color sensors. For the sonar sensors, one was placed at the top and the other placed by the side of the robot. The concept we wanted to implement with these two sensors was to use the top sonar sensor for front obstacle (wall) detection and the side sensor for side obstacle (wall) detection and avoidance.

Also, one color sensor faced downwards while the other was place in front of the robot. With the front color sensor detecting, finding and recording the color of a bottle and its color the downward color sensor would use that data to find the respective collection zone that has the same color as the bottle detected.

  • For our solution concept, the process goes like;
  1. Do random exploration in the environment to find colored bottles while avoiding obstacles.
  2. On finding bottle, save color of the bottle, grab the bottle and move along the wall of the environment.
  3. When the appropriate color zone is detected, drop bottle.
  4. Continue with the random exploration.

Implementation

Our first step in the implementation stage was building our robot. The robot had to have arms to enable grabbing of the bottles. The arm that was meant to grab the bottles needed a motor to control the opening and closing of the arms. The color sensors were placed in front of the robot in between the arms with one sensor horizontally positioned to detect the color of obstacles in front of the robot. Another color sensor was place vertically, so that it the sensing area pointed down, in order to detect the color of the landing zones.

The next step was programming the robot to use its sonar sensor inputs to do wall-following. This we programmed using the Bang-Bang and P control mechanisms. Though the wall following program worked along a straight wall, it failed in the treasure hunt environment because of the acute angular nature of the boundaries. With that situation, we had to implement a wall avoidance procedure (solution) to enable the robot travel successfully through the environment without bumping into the walls. A solution that would use an extra sonar sensor to prevent head-on collision was implemented and that necessitated the use of two sonar sensors on tribot. The sonar sensors on the robot needed to be positioned at a particular angle to allow both of them to work in synchronization based on the code and logic implemented. A number of tests helped determine the appropriate position for the sonar sensors and appropriate sonar values.

With regard to the Programming algorithm, this is the approach

->reset claw ()

->start exploration task ()

->start avoidance task ()

–>avoid front collision ()

–>avoid side collision ()

–>avoid going outside the assigned environment ()

->while search isn’t ended {

–>if treasure is detected {

—>start grab and Deposit ()

–>}

->}

View of our Treasure hunter robot

View of our Treasure hunter robot

Challenges

One major challenge encountered was with the alternative wall avoidance procedure. This solution did a great job of avoiding obstacles but the robot kept avoiding the treasures also and followed along the same route close to the walls of the environment. There was no randomness in the exploration and just a little section of the total surface area of the environment was being covered. This problem was fixed by programming the robot to turn after every front obstacle detection and hence obstacle avoidance. This introduced some randomness and the robot covered more surface area, however, this did not fix the issue of the robot avoiding the treasures themselves.

The other challenge was with the coverage area of the color sensors that made detecting a treasure quite difficult. The color sensor needs to be very close to the object of interest in order to accurately determine the color of the object. Also, the sensors had a narrow field of view and thus the object of interest needed to be directly in front of the sensor to make a successful detection. This makes the robot pass by and knock down treasures that are in its path but not directly in front of the color sensor. This problem has not being fixed and chance is really the deciding factor in the detection and recognition of a treasure.

The approach used in exploring and searching for treasures was a random one and this came with the problem of time inefficiency. As the number of treasures in the environment decreases the time taken to detect a treasure increases. The exploration bit of the program relied on obstacle avoidance till the robot came on a path that would allow the front color sensor detect a treasure (a bottle). Attempts to fix this problem would demand a major change in the concept of the solution and the structural design of the robot.

Conclusion

Looking at the design concept and its implementation we found iterative testing to be key in making our robot more efficient and reliable. The placement of the sonar sensors was very important since placing them at the wrong position would give unreliable results due to the noisiness that comes with the some sensors such as the sonar sensors.

The whole task taught us a few lessons which were very important in building and programming a robot to perform tasks. One challenge we faced was testing and making sure the robot is reliable in hunting for the treasures (bottles) and that is it could perform the same task over and over again without encountering any problems.

Another challenge was breaking down the whole treasure hunt task into small problem units and testing them to make sure each “sub-task” such as wall-following was working very well before moving on to say, treasure (bottle) detection. Overall, the task taught us the essence of first breaking down the whole task into smaller task and solving them unit by unit.

 

Relevance to Problem Solving in Ghana

This treasure hunt concept can be implemented in areas of accidents where victims cannot be located or reached to offer help to them. For example during the recent collapse of the  one Melcom shop branch in the country, health and security personnel were not able to find or locate victims due to their inability to enter the rubble.

Robots can be programmed with the proper sensors such as a camera to help detect where victims are located in an accident. This would not only hasten the work of security and health personal but saves lives as well.

 

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