Robotic dolphins and sharks and fish-like robots with embodied artificial intelligence
A robotic dolphin and shark empowered by generative artificial intelligence (Gen-AI) are disclosed, capable of autonomously performing essential tasks such as marine research, environmental monitoring, and underwater inspections. The robotic dolphin's lifelike design includes a head with snout, eyes, mouth, blowhole, body, pectoral fins, dorsal fin, and tail fin, all meticulously crafted to mimic the appearance and behavior of a real dolphin. A trained AI model functions as the brain, processing environmental data captured by video cameras, audio microphones, and sensors to provide guidance commands to a control system that controls the movements of the robotic dolphin. A well-trained live dolphin can serve as a teacher for one or multiple robotic dolphins using a generative AI-based real-time training method, enabling efficient and effective training of robotic dolphins.
1 . A fish-like robot comprising:
a) a body comprising:
(i) a head;
(ii) a plurality of eyes;
(iii) a body structure to house or connect robot components;
(iv) a plurality of fins; and
(v) a tail;
b) a plurality of sensors configured to capture environmental data, including at least one video camera, at least one audio microphone, and at least one swimming sensor;
c) a power supply;
d) a guidance and control system comprising a trained and continuously updated artificial intelligence (AI) model using underwater behavioral patterns and actions of a real fish, wherein the guidance and control system is configured to process the environmental data captured by the sensors and generate control signals; and
e) a plurality of actuators responsive to the control signals generated by the guidance and control system, wherein the plurality of actuators are configured to manipulate at least the plurality of fins and the tail to perform autonomous swimming and underwater grasping.
2 . The fish-like robot of claim 1 , wherein the plurality of eyes comprises at least one camera and one sonar sensor.
3 . The fish-like robot of claim 1 , further comprising a wireless communication module configured to transmit data captured by the plurality of sensors to a remote monitoring station.
4 . The fish-like robot of claim 1 , wherein the plurality of sensors further comprises environmental sensors configured to measure temperature, pressure, depth, and salinity.
5 . The fish-like robot of claim 1 , wherein the guidance and control system comprises a navigation module configured to use GPS signals for determining a location and path of the fish-like robot.
6 . The fish-like robot of claim 1 , wherein the power supply comprises a battery and a wireless charging system allowing the fish-like robot to charge the battery autonomously.
7 . The fish-like robot of claim 1 , wherein the plurality of fins and the tail further comprise actuators configured to adjust the plurality of fins and the tail.
8 . The fish-like robot of claim 1 , further comprising a plurality of robot arms that can be extended and controlled from the body of the fish-like robot to perform tasks.
9 . The fish-like robot of claim 1 , wherein the fish-like robot is a dolphin-like robot.
10 . The fish-like robot of claim 1 , wherein the fish-like robot is a shark-like robot.
11 . A guidance and control system of a fish-like robot, comprising:
a) a plurality of sensors configured to capture environmental data, the sensors comprising at least one video camera, at least one audio microphone, and at least one swimming sensor;
b) an artificial intelligence (AI) model trained and continuously updated using underwater behavioral patterns and actions of a real fish and configured to process the environmental data captured by the plurality of sensors and provide the fish-like robot swimming and motion guidance;
c) a computing processing unit configured to execute the AI model, control algorithms, and provide guidance commands and control signals; and
d) a plurality of actuators responsive to the control signals, wherein the plurality of actuators are configured to manipulate parts of the fish-like robot to perform autonomous swimming and underwater grasping.
12 . The guidance and control system of claim 11 , wherein the guidance and control system is configured to perform obstacle detection and avoidance using data from the plurality of sensors.
13 . The guidance and control system of claim 11 , wherein the AI model is further configured to optimize swimming paths based on real-time environmental data.
14 . The guidance and control system of claim 11 , further comprising a wireless communication module configured to transmit data to, and receive data from, a remote monitoring station.
15 . The guidance and control system of claim 11 , further comprising a GPS module configured to provide location data for navigation and swimming control of the fish-like robot.
16 . The guidance and control system of claim 11 , wherein the plurality of actuators are further configured to adjust a plurality of fins and a tail of the fish-like robot.
17 . A robotic dolphin online training system, comprising:
a) a live video capture system configured to capture real-time video data of behaviors of a real dolphin;
b) a data processing unit configured to process the captured video data and extract key behavioral patterns and actions of the real dolphin;
c) a generative artificial intelligence (AI) model configured to analyze the processed data and learn underwater behaviors, movements, and responses of the real dolphin;
d) a real-time adaptation system configured to allow a robotic dolphin to implement learned behaviors including underwater grasping and adapt in real-time; and
e) a continuous learning system configured to update the AI model with new data from activities of the real dolphin.
18 . The robotic dolphin online training system of claim 17 further configured to seamlessly integrate with a guidance and control system of the robotic dolphin.
19 . The robotic dolphin online training system of claim 17 , wherein the real-time adaptation system comprises a feedback mechanism to adjust behaviors of the robotic dolphin based on real-time interactions and responses from the real dolphin.
20 . The robotic dolphin online training system of claim 17 , wherein the AI model can be saved and copied for use with other robotic dolphins to produce more trained robotic dolphins.