The document presents an obstacle avoidance algorithm for mobile robots that uses ultrasonic sensors to detect obstacles and then implements the Bug 1 and Bug 2 algorithms to navigate around obstacles in a reactive manner. It describes the Bug algorithms, compares Bug 1 and Bug 2, and discusses other algorithms like VFH and potential fields. Potential applications of obstacle detection algorithms discussed include mining vehicles, smart cars, and autonomous cleaning robots.

1. Submitted by
1. Sojal, Md. Jahidul Hasan 12-22626-3
2. Taufiquzzaman, Md. 14-25506-1
3. Islam, M. Jamiul 14-26006-1
4. Rahman, Md. Mustafizur 14-27279-2
5. Khan, Md. Tasdikul Islam 15-29210-1
Submitted to
Rethwan Faiz
Assistant Professor,
Department of EEE.
American International University-Bangladesh
Real-time Obstacle Avoidance
Algorithm for Mobile Robots

2. ROBOTICS ALGORITHM
Welcome
to the
Presentation !!!

3. •Introduction
•Flow Chart
•Algorithm Overview
•Diagrams
•Implementation
•References
OVERVIEW

4. INTRODUCTION
This type of robot gets the information from
surrounding area through mounted sensors on the
robot. Some sensing devices used for obstacle detection
like infrared sensor, ultrasonic sensor etc.
Ultrasonic sensor is most suitable for obstacle detection
and it is of low cost and has high ranging capability.

5. FLOW CHART

6. ALGORITHMS
The BUG Algorithms
The simplest obstacle avoidance algorithm ever described is
called “the bug algorithm”. According to it, when an obstacle is
encountered, the robot fully circles the object in order to find the
point with the shortest distance to the goal.

7. ILLUSTRATION

8. • Very Easy to Implement
• Costs lower in terms of implementation then other
algorithms
• Works very good in simple scenario
ADVANTAGES

9. DISADVANTAGES
• It considers only the most recent sensor readings, and
therefore sensor noise seriously affects the overall
performance of the robot
• It works very slow
• Result is complex scenario is very poor

10. PSEUDO CODE

11. CODE

12. BUG 2 ALGORITHM
• More improvised
• Follow greedy search technique
• Faster then BUG 1 Algorithm
• More time efficient
• But not as predictable as BUG 1 Algorithm

13. BUG 1 vs. BUG 2
Figure: BUG 1 Algorithm Figure: BUG 2 Algorithm

14. BUG 1 vs. BUG 2
• BUG 1 is an exhaustive search algorithm, it
looks at all choices before committing
• BUG 2 is a greedy algorithm, it takes the first
thing that looks better
• In many cases, BUG 2 will outperform BUG 1,
but BUG 1 has a more predictable performance
overall

15. • The Vector Field Histogram (VFH)
Algorithm
VFH algorithm overcomes the
problem of the sensors noise by
creating a polar histogram of several
recent sensor readings, which was one
of the major problem of BUG
Algorithm
Fig: The polar histogram used
in VFH algorithm
OTHER ALGORITHMS

16. • The Potential Field Algorithm
While the bug-type algorithms are
based on a purely reactive approach,
the following algorithms tend to view
the obstacle avoidance as a sub-task of
the path planning, in a deliberative
approach.
OTHER ALGORITHMS
(CONTINUED)

17. •The Bubble Band Technique
With this concept, a band of such
bubbles can be used to plan a path
between a starting point and a goal.
Obviously, this technique is more a
problem of offline path planning
than one of obstacle avoidance
OTHER ALGORITHMS
(CONTINUED)

18. • As a Mining Vehicle
Reliable obstacle detection is an essential element of an autonomous mining vehicle
system. An autonomous vehicle must be capable of detecting potentially dangerous
obstacles that would endanger the vehicle itself.
• Smart Motor Vehicle
Already few smart vehicle projects have been developed and under monetization. They are
using lots of advanced methods and Artificial Intelligence where obstacle detection is a
vital part.
• Autonomous cleaning robot
There is a long felt need for autonomous robotic cleaning devices for dusting, mopping,
vacuuming, and sweeping operations. Although technology exists for complex robots
which can, to some extent, "see" and "feel" their surroundings, the complexity, expense
and power requirements associated with these types of robotic subsystems render them
unsuitable for the consumer marketplace.
USES

19. REFERENCES
•https://www.livescience.com/topics/robots
•https://www.robotictechnologyinc.com/
•http://www.popularmechanics.com/technology/robots/
•https://www.mouser.com/applications/robotics-technology/
•http://study.com/directory/category/Engineering/Electrical_Engin
eering_and_Electronics/Robotics_Technologies.html