Abstract:
This project investigates the general robots behavior, control and Multi-Sensor sensory fusion
techniques using low cost Infra-red (1R) sensors, Sonar sensors (Ultrasonic sensors), Optical
encoders and general-purpose Web camera specially CMUcam CMOS camera.
According to my literature survey 1 have found that current high - tech researches are going on
by applying very expensive and sophisticated sensory devices such as, Stereo-Vision sensors,
Laser scanners, High resolution CCD camera etc. along with embedded high speed Digital
Signal Processor (DSP) systems. Due to above technical and financial restrictions facing with
research as well as depth of expected research study to be performed; very complex and highly
expensive components should have been eliminated and would not be illustrated further.
This project particularly based on sensory fusion with image processing techniques. The
objective as well as motivation is, to build a low cost, optimal level resource consuming reliable
sensory system for a robot. Relying only one sensor especially the time - of flight sensor
(sonar) will probably cause problems such as, sonar sensors are limited in resolution, range and
the size of the object they can detect, sensor value (from sonar) may not correspond to the actual
distance of the object, cross talk, fore shorting and specula reflection.
Sensors sometimes can be complementary or redundant since it is necessary to make an
appropriate selection of sensors when building the sensor suit for a mobile robot. For an
example, Infra-Red (IR) can provide less-accurate range measurements compared to the
ultrasonic sensors but IR sensors can provide a large number of measurements in a short time
period; can easily be mounted on a scanner to provide panoramic view and sonar sensors are
excellent for mobile robot applications when especially navigate through a room filled with
obstacles. In many cases multiple sensor sources are better than single sensor reading. This led to
the development of the sensor system architecture with sensory fusion techniques. Further, this
permits more than one sensor making the sensory system more reliable and robust.
Typically the general architecture of the fusion sensor has been categorized into two; low-level
fusion and high-level fusion. In this project, the architecture is developed based on actionoriented
sensory fusion, in belief that multiple sensor reading can be fused and would give rise to
certain behavior for mobile robot. And also Filtering techniques are employed to reduce the
uncertainties in the line segment representation and Data / Image fusion.
Some of the issues in designing particular vision system for the robot, involves capturing and
storing the entire image before starting the image analysis and to overcome some of general
vision system issues, system has to be designed to extract visual information from the
environment in Real-Time using an affordable 'off - the - shell' digital CMU cam color camera
and embedded controller.
The final implementation and results were obtained by using Simrobot simulations and real low
cost mobile platform was developed to certify the trialed simulations and implemented
behaviors. It is discussed that complex situations such as emergency behavioral decision making,
significantly deviates from expected once so that vision and image processing in real time make
hardcore experience in low cost camera 1 had used and also uncertainty of sensor inputs truly
make unexpected fusion results with noise addition as well.