Bio-Inspired Quadruped Robots: Autonomous Navigation In Dynamic Environments

This paper presents a novel approach to autonomous navigation for an insect-inspired bio-mimetic quadruped robot in dynamic unknown environments. The proposed navigation system integrates a behavior-based control algorithm, combining goal attraction, obstacle avoidance, and wall-following strategies to enhance adaptability of quadruped robots in dynamic environments. The robot is modeled as a unicycle to simplify control, allowing it to track reference trajectories using only linear and angular velocities. A multilayer control architecture is employed, transforming high-level navigation decisions into joint-level commands for real-time locomotion. Simulation results demonstrate the robot's ability to achieve real-time path planning, maintain safe distances from obstacles, and exhibit efficient locomotion even in obstacle-rich and dynamic environments. This study offers a robust solution for enhancing the autonomy and adaptability of quadruped robots, with significant implications for applications in search and rescue, exploration, and medical assistance.