Collision avoidance technique using bio-mimic feedback control

Collision avoidance is a major area of research in vehicle control & safety that involve varying degrees of uncertainty. In general, this problem is challenged with forward collision avoidance technology (FCAT) in cars. An intelligent technique that complements the driving experience must work to avoid collisions generating a smooth trajectory, the vehicle to the intended destination as quickly as possible. Unfortunately, satisfying these requirements with traditional methods proves intractable and forces us to consider bio mimic techniques like Swarm Intelligence. We have developed a bio-tracking based hybrid model which follow the behavior of Ant (tapinoma melanocephalum) and Bat (molossus molossus). In this research, our robot detects obstacle with ultrasound like bat and makes decision to avoid the obstacle like ant. Here an Ultrasonic sound (SONAR) reflection based intelligent control strategy is implemented. Depending on Bat object tracking and Ant motion strategy, we have successfully avoided collision between prototype vehicles and obstacles which was our first goal. This natural sense building up in mechatronics world could make life more secure and find out a perfect relation between theoretical mathematics, nature and engineering.