Robotics + AI Integration

Learn how to build intelligent robotic systems by combining mechanical engineering with artificial intelligence concepts.

Core Robotics + AI Concepts

Perception Systems

Integrate computer vision and sensor data processing for real-time object detection and spatial awareness.

Decision Making

Use AI algorithms for path planning, task prioritization, and autonomous navigation solutions.

Actuators & Control

Implement motor control systems and real-time response to environmental inputs.

Project Examples

Autonomous Navigation

Teach robots to navigate complex environments using SLAM algorithms and reinforcement learning techniques.

# Sample Python code import numpy as np from sensor import LIDAR sensor = LIDAR() while True: data = sensor.read_environment() print(f"Obstacles detected: {np.count_nonzero(data > 0)}")

Object Grasping

Develop robotic arms that recognize and pick objects using computer vision and torque-based control systems.

85% success rate 35 hours trained

Ready To Build Intelligent Robotics

Combine robotics engineering with modern AI techniques to create smart systems that learn, perceive, and adapt.

Start Learning Robotics View Example Projects