Quantifying the control laws governing terminal attack in lions.

Intercepting an evasive, maneuvering target is among the most computationally demanding tasks a predator performs: in the terminal phase of a chase, it must continuously convert sensory information about the target into steering and speed commands, subject to its own biomechanical limits. How terrestrial predators solve this in real time has remained difficult to quantify. Here, we combine drone videography with AI-based markerless pose estimation to reconstruct the kinematics of 67 lion (Panthera leo) attacks on a mechanized lure programmed to move unpredictably. Lion steering is described by a combination of proportional navigation and proportional pursuit, which is a mixed guidance law previously identified only in the aerial pursuit of Harris's hawks (Parabuteo unicinctus), and speed is regulated within a defined kinematic envelope during turns, which declines at close range where the cost of overshooting is greatest. These findings reveal shared guidance principles across aerial and terrestrial pursuit, thus providing a quantitative framework for comparing pursuit strategies across species.