L-BIRD: Lightweight Bio-Inspired Rotary-Wing Drone

Abstract

In nature, birds exhibit outstanding attitude control, enabling flexible and efficient takeoff, hovering and landing — capabilities that have not been fully replicated. Thus, we introduce the lightweight bio-inspired rotary-wing drone (L-BIRD). It incorporates a spherical structure, which can imitate birds' attitude variation and land on complex surfaces adaptively. L-BIRD employs a model predictive control (MPC) framework to enable real-time tracking of bird-like attitude trajectories derived from bio-inspired parameter pairs. To facilitate lightweight deployment on resource-constrained hardware platforms, we improve MPC framework by multi-path primal-dual neural network (PDNN), matrix sparsity and multiplicative optimization. Experimental results, both in simulations and real-world deployments, demonstrate that L-BIRD realizes accurate and efficient biomimetic attitude control and diverse environmental adaptability. The attitude trajectory mean-square error (MSE) decreases to 0.0042, rd, random access memory (RAM) usage reduces by 39.3%.