Traditional mechanical robots, despite marked advances in intelligence and structural diversification, are vastly outperformed by living animals in mobility, autonomous decision-making, endurance, and adaptability to unstructured complex environments, even with integrated machine learning. Cyborg animals bridge this gap by deeply integrating machine and biological intelligence, using external artificial stimulation to direct organisms to execute human commands while retaining their natural advantages of exceptional environmental adaptability, powerful self-healing, and ultra-high energy conversion efficiency. The field was formally founded in 1997, when researchers first achieved artificial locomotion control of live cockroaches via electrical stimulation, and has since expanded from early insect and rat models to a diverse array of vertebrate and invertebrate species.
The review organizes research progress through animal taxonomy: vertebrates including rats, pigeons, fish, and reptiles are primarily researched via brain-computer interface (BCI) technology, with rats as the gold standard for BCI clinical translation, pigeons engineered for aerial navigation control, and fish adapted for underwater exploration. For invertebrates, arthropods such as beetles, cockroaches, moths, and locusts dominate research, with muscle-receptor electrical stimulation as the core control method, perfectly suited to their small size and simple neuromuscular systems. The paper details two dominant control paradigms: BCI-based brain region stimulation for high-level behavioral control of complex vertebrates, and direct muscle and sensory receptor electrical stimulation for precise, minimally invasive control of small invertebrates, alongside supplementary techniques including visual, chemical, thermal, and optogenetic stimulation.
Critical hardware advances center on miniaturized, low-power electronic backpacks—the core control hub for all cyborg animals—optimized for terrestrial, aerial, and aquatic use, with weights reduced to as little as 0.42 grams for moth models, paired with breakthroughs in biocompatible microelectrodes, onboard situational awareness sensors, and self-sustaining energy harvesting technologies. Navigation algorithms have evolved from single-animal closed-loop control to swarm coordination, with AI and reinforcement learning enabling efficient collaborative navigation of cyborg cockroach swarms in unknown, obstructed terrains.
From lab to real-world application, cyborg animals reached a historic milestone in 2025, when 10 cyborg cockroaches completed the world's first practical disaster relief operation in an earthquake in Myanmar. The technology also holds transformative potential in environmental exploration, brain-controlled human-machine interaction, and unmanned system collaboration, with future applications spanning ecological monitoring, hazardous environment reconnaissance, and precision agriculture.
The review also identifies core unresolved challenges: inconsistent control efficacy driven by biological individual variability, the long-term biocompatibility of implanted electrodes, and payload and endurance limitations of miniature hardware. Critically, it emphasizes that ethical regulation and strict adherence to the 3Rs (replacement, reduction, refinement) principle of animal welfare are indispensable to responsible research, calling for a standardized ethical framework to balance scientific progress and moral responsibility, and ultimately advance the development of integrated human-machine-animal hybrid intelligent systems.
Authors of the paper include Yue Ma, Chuang Zhang, Fei Nie, Hengshen Qin, Qi Zhang,
Yiwei Zhang, Lianchao Yang, and Lianqing Liu.
This work was supported by the National Natural Science Foundation of China (62373347, 62525301 and 62333021), the New Cornerstone Science Foundation through the XPLORER PRIZE, the CAS Project for Young Scientists in Basic Research (YSBR-041), the Youth Innovation Promotion Association of CAS (2023210), the Natural Science Foundation of Liaoning Province (2024JH3/10200028), the State Key Laboratory of Robotics and Intelligent Systems (2024-Z04), the Fundamental Research Project of SIA (2022JC2K01 and E4391103), and the Jiang Xinsong Young Seedlings Fund of SIA.
The paper, "Construction, Control, and Application of Cyborg Animal Composed of Biological and Electromechanical Systems" was published in the journal Cyborg and Bionic Systems on Mar. 26, 2026, at DOI: 10.34133/cbsystems.0486.
