IIT researchers decode animal homing behaviour to help autonomous navigation

A team of Indian researchers has used programmable robots to study animal homing behaviour and concluded that optimal randomness, combined with occasional resets, enhances navigation efficiency. The findings of the study could help autonomous vehicle navigation, search, and rescue missions, and offer insights into cellular dynamics, researchers say.

The ability to return home after activities like migration or foraging is crucial for many animals. Homing pigeons are renowned for their ability to deliver messages over long distances due to their exceptional navigation skills. Similarly, sea turtles, salmon, and monarch butterflies undertake long journeys to return to their birthplaces. This homing behaviour, common in nature, has long intrigued scientists.

The research provides new perspectives on the physics of homing and opens avenues for further exploration in both biological and technological contexts.

Different species use various strategies to achieve homing. Some rely on path integration, calculating their return based on the distance travelled and direction, while others depend on environmental cues such as smells, landmarks, star positions, or the Earth's magnetic field. Despite these varied methods, homing is a highly efficient process. However, the influence of random factors, or "noise," on animal navigation remains an area of ongoing research.

The research team investigated these patterns using small robots designed to mimic animal behaviour. These robots, around 7.5 cm in diameter, were equipped with sensors to detect objects and light, enabling them to locate a "home" marked by the brightest light source. The robots navigate using independently controlled wheels and adjust their paths based on light intensity, similar to certain animals.

The researchers found that beyond an optimal level of randomness, the duration of homing remains unaffected. Computer simulations further supported these findings, revealing that occasional 'resets,' where the robots reoriented directly toward home, enhanced their ability to correct their paths.

"These findings could inform the development of better navigation systems for autonomous vehicles and improve search and rescue missions. Additionally, the study offers valuable insights into cellular dynamics, where similar processes might be at play," Harsh Soni, Assistant Professor, School of Physical Sciences, IIT Mandi, said.

The theoretical and numerical aspects of the research were conducted by Harsh Soni from the Indian Institute of Technology (IIT) Mandi, along with Arnab Pal and Arup Biswas from The Institute of Mathematical Sciences, Chennai. The experimental work was led by Nitin Kumar and Somnath Paramanich from IIT Bombay.