Astrodon's Biological Characteristics and Brain-Computer Interface Technology

Design of a Quadrupedal Bionic Intelligent Prospecting Robot for the Wetland-Forest Ecotone of the Early Cretaceous (approx. 112 million years ago) Arundel Formation, Integrating Astrodon's Biological Characteristics and Brain-Computer Interface Technology

This design proposes a quadrupedal bionic intelligent prospecting robot, systematically innovating across five dimensions: bionic morphology adaptation, environmental perception and navigation, intelligent task execution, brain-computer interaction integration, and energy and protection, tailored for the specific environmental characteristics of the Arundel Formation and the biological traits of Astrodon.

I. Bionic Morphology and Locomotion System: Adapted to Wetland-Forest Environment
• Quadrupedal Bionic Structure: Mimicking Astrodon's quadrupedal gait, featuring an "elephant-foot-sloth claw" composite design. The feet consist of wide, elastic pads (with embedded pressure sensors and terrain-adaptive hydraulic systems) to enhance wetland grip and swamp traversal capability. Retractable hook-like claws (similar to sloth claws) are located between the toes for climbing trees or excavating soft sediments. Joints employ a bionic shock absorption system (e.g., hydraulic damping + shape-memory alloys) to reduce vibration loss during long-distance travel.

• Functionalized Neck and Tail: The neck utilizes retractable carbon fiber composite materials (extendable up to 3 meters), equipped with a multi-degree-of-freedom robotic arm (tip integrated with a micro drill, gripper, and micro-CT scanner) for remote fossil excavation or high-branch sample collection. The tail integrates a balance gyroscope and a flexible solar panel (22% efficiency), maintaining locomotion stability while supplementing energy via high-intensity sunlight.

• Streamlined Torso Design: The outer layer is covered with a nano hydrophobic coating and dust-proof seals to prevent wetland mud and sand from invading core components. An internal liquid metal cooling circulation system maintains stable operation under extreme temperature differences (surface 35°C to nighttime 5°C).

II. Environmental Perception and Navigation System: Precise Positioning and Obstacle Avoidance
• Multi-modal Sensor Array:

◦   Terrain Perception: LiDAR (accuracy ±1mm) + Ground Penetrating Radar (detection depth 5m) for 3D reconstruction of rock layers and precise fossil localization.

◦   Environmental Monitoring: Infrared thermal imager (detection range -20°C to 150°C), gas detector (identifying toxic gases like methane, hydrogen sulfide), humidity sensors, and soil hardness sensors for real-time Cretaceous environmental data acquisition.

◦   Biosignal Detection: Bioelectric sensors and sound recognition modules to monitor faint biological signals (e.g., from insects, small reptiles), assisting ecological interaction studies.

• Intelligent Navigation Algorithms: Combines SLAM algorithms with AI path planning to autonomously plot optimal exploration paths, avoiding hazardous areas like swamp traps and cliffs. Collaborates with a cloud AI platform via 5G/6G networks, using deep learning for large-scale terrain modeling and fossil distribution prediction.

III. Intelligent Task Execution Module: Excavation, Sampling, and Special Tasks
• Excavation and Sampling System:

◦   Intelligent Drilling Module: Utilizes ultrasonic vibration-assisted drilling technology, coupled with a variable-stiffness robotic arm, adaptable to drilling needs in rock layers of different hardness (e.g., sandstone, shale). The drill bit incorporates a micro-camera and pressure sensors for real-time feedback on drilling resistance and stratum changes, preventing fossil damage.

◦   Sample Processing Module: Includes built-in non-destructive analyzers (e.g., XRF spectrometer, micro-Raman spectrometer) and a micro-lab for in-situ component analysis, dating (e.g., uranium-lead dating), and morphological scanning of samples. Data is transmitted in real-time to the cloud for AI-driven fossil classification and geological feature identification.

• Special Task Execution:

◦   Ecological Monitoring: Uses bioelectric sensors and sound recognition technology to monitor biological activities within the Cretaceous ecosystem, aiding research into evolution and ecological interactions.

◦   Emergency Rescue: Carries a foldable rescue pod and medical-grade life support systems for rescuing personnel in extreme environments.

IV. Brain-Computer Interface Integration: Deep Human-Machine Fusion
• Semi-Invasive BCI: Employs transcranial electrical stimulation (tES) combined with high-precision electroencephalography (EEG) to decode human intent (e.g., "advance," "drill," "sample") in real-time, with latency controlled below 80ms. A closed-loop feedback mechanism converts environmental data (e.g., terrain resistance, temperature changes) into electrical signals fed back to the user's brain, forming a "perception-decision-execution" closed-loop interaction.

• Intelligent Decision-Making and Autonomy: The robot contains an edge computing unit (e.g., NVIDIA Jetson AGX Orin) to process real-time data (e.g., image recognition, path planning), reducing communication latency with the cloud. Through reinforcement learning algorithms, the robot continuously optimizes its behavior patterns (e.g., adjusting drilling parameters, optimizing paths) during task execution, increasing intent recognition accuracy to over 95%.

V. Energy and Protection System: Sustainability and High Reliability
• Hybrid Energy Supply: Combines dorsal solar panels (22% efficiency) with a miniature nuclear battery (e.g., Plutonium-238 Radioisotope Thermoelectric Generator) to ensure sustained operation without sunlight or in extreme environments. Built-in supercapacitors support short-term high-power output (e.g., emergency drilling), and wireless charging technology enables rapid energy replenishment (charging time ≤ 30 minutes).

• Protection and Reliability Design: The outer layer features a bionic scale structure (high-strength ceramic composite + self-healing polymer coating) capable of repairing cracks ≤ 5mm in diameter. The core control unit employs a triple redundant architecture. Critical components (e.g., sensors, power units) use a hot-swappable design for quick replacement. A built-in AI diagnostic module continuously monitors hardware status and software anomalies, sending alerts to the user via the BCI (e.g., power unit overload, sensor failure).

VI. Application Scenarios and Scientific Value
This robot is applicable in Early Cretaceous geological prospecting, paleontological fossil excavation, and extreme environment scientific research. For example, within the wetland-forest ecotone of the Arundel Formation, the robot can precisely locate Astrodon fossil burial sites, enabling remote operation by archaeologists via the BCI, avoiding damage caused by traditional excavation methods. Coupled with real-time collection of Cretaceous environmental data (e.g., climate, vegetation, geological activity), it provides high-precision data support for paleoclimate reconstruction, biological evolution research, and studies on adaptation mechanisms in extreme environments, thereby advancing the understanding of Cretaceous ecosystems and evolution.

Through the above design, this bionic intelligent robot not only possesses high-efficiency exploration and excavation capabilities within the complex environment of the Early Cretaceous but also achieves deep integration of the human brain and machine via the brain-computer interface, offering a revolutionary technological tool for paleontology, geology, and extreme environment research.