IIT Mandi's study leverages AI to decode homing behaviour in animals. The institute's researchers have made significant advances in understanding how animals navigate back home. They explored the complexities of homing behaviour within a controlled environment using small, programmable robots. The findings of the study have been published in the journal PRX LIFE. The theoretical and numerical aspects of the research were conducted by Dr Harsh Soni from IIT Mandi, along with Dr Arnab Pal and Mr Arup Biswas from The Institute of Mathematical Sciences, Chennai. The experimental work was led by Dr Nitin Kumar and Mr Somnath Paramanich from IIT Bombay.

The ability to return home after activities like migration or foraging is crucial for many animals. Homing pigeons, for example, 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.

According to Dr. Harsh Soni, Assistant Professor at the School of Physical Science, these findings could inform the development of better navigation systems for autonomous vehicles and improve search and rescue missions. The study offers valuable insights into cellular dynamics, where similar processes might be at play. 

Meet the team behind the research

Finding patterns

Different species use various strategies to achieve homing. Some rely on path integration, calculating their return based on the distance travelled and direction. In contrast, others depend on environmental cues such as smells, landmarks, star positions, or the Earth's magnetic field. Despite these varied methods, homing is typically 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 that mimic animal behaviour. These robots, approximately 7.5 cm in diameter, are 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 team found that beyond an optimal level of randomness, the homing duration 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.

The researchers believe that the study provides new perspectives on the physics of homing and opens avenues for further exploration in biological and technological contexts.