Selfnavigation

Self-navigation refers to the ability of an organism or a system to determine its own position and orientation within an environment and to plan and execute a course of movement towards a desired goal. This capability is fundamental to survival and has evolved across a wide range of biological and artificial entities.

In biological organisms, self-navigation relies on a complex interplay of sensory input and internal processing. Sensory organs like eyes, ears, and olfactory receptors gather information about the external world, which is then processed by the nervous system. This information is integrated with internal cues, such as proprioception (the sense of the relative position of one's own parts of the body) and memory, to create a representation of the environment and the organism's location within it. Navigation strategies can range from simple stimulus-response behaviors to sophisticated cognitive mapping and pathfinding.

Artificial systems, such as robots and autonomous vehicles, also employ self-navigation. These systems typically use sensors like GPS, lidar, cameras, and inertial measurement units (IMUs) to perceive their surroundings. Algorithms are then used to process this sensor data, estimate the system's state (position, velocity, orientation), and plan a trajectory to reach a target destination. Challenges in artificial self-navigation include dealing with sensor noise, dynamic environments, and computational constraints. The study of self-navigation, both biological and artificial, draws on principles from neuroscience, computer science, engineering, and ethology.