Description

Robot automatic maps (Source code exist at download)

Autonomous Robotic System for Exploration and Mapping of Unknown Environments with Real-Time Wireless Communication.

Abstract— This work presents the design and implementation of an autonomous robotic system for the exploration and mapping of unknown environments. The system employs a structured navigation algorithm combined with real-time obstacle detection and wireless data transmission. It is capable of systematically scanning an area, dynamically extending its coverage, and safely returning to its initial position upon completion. The implementation is based on low-cost embedded hardware and demonstrates efficient integration of sensing, navigation, and communication subsystems. Index Terms— Autonomous robotics, mapping, obstacle detection, Arduino Uno, ESP8266, wireless communication I. INTRODUCTION Autonomous exploration and mapping constitute fundamental challenges in the field of mobile robotics, with applications in search and rescue, surveillance, and environmental monitoring. This paper presents the development of a compact robotic system capable of navigating unknown environments while providing real-time feedback through a wireless interface. II. SYSTEM ARCHITECTURE The proposed system is based on a modular embedded design and consists of two primary hardware components: · Arduino Uno, which serves as the main microcontroller responsible for motion control, sensor data acquisition, and execution of the navigation algorithm. · NodeMCU ESP8266, which provides Wi-Fi connectivity and hosts an embedded web server for real-time monitoring. The robotic system operates autonomously without requiring continuous external control, forming a fully wireless robotic platform. III. NAVIGATION AND MAPPING ALGORITHM The navigation strategy follows a deterministic square traversal pattern. Initially, the robot maps a unit square area and progressively expands the exploration radius, enabling coverage of larger spaces. Obstacle detection is continuously performed using onboard sensors. When an obstacle is identified, its presence and relative distance are recorded and transmitted in real time. A key feature of the system is the implementation of a manually structured internal database embedded within the code. This database stores movement sequences and positional references, allowing the robot to reconstruct its trajectory and reliably return to its initial starting position after completing the exploration process. IV. COMMUNICATION AND USER INTERFACE The ESP8266 module hosts a lightweight web server, enabling real-time interaction between the robotic system and the user via Wi-Fi. The web interface provides: · Real-time system status monitoring · Visualization of detected obstacles · Distance measurements relative to the robot Data transmission is performed on-the-fly, ensuring low-latency communication between the system and external devices. V. SYSTEM OPERATION The overall operation of the system can be summarized as follows: 1. Initialization of sensors and communication modules 2. Execution of the square-based exploration algorithm 3. Continuous obstacle detection and logging 4. Real-time wireless data transmission 5. Storage of movement data in the internal database 6. Completion of the mapping procedure 7. Autonomous return to the starting point using stored data base path information VI. IMPLEMENTATION DETAILS The system is implemented in embedded C/C++ using the Arduino development environment. For academic integrity purposes, the source code is provided in an obfuscated (non-readable) form while maintaining its functional behavior for evaluation. VII. CONCLUSION This work demonstrates an effective approach to autonomous exploration and mapping using low-cost hardware and a structured navigation algorithm. The integration of real-time communication, obstacle detection, and return-path capability highlights the potential for scalable and adaptable robotic systems in real-world applications. VIII. FUTURE WORK Future improvements may include the integration of advanced mapping techniques (e.g., SLAM), enhanced obstacle avoidance algorithms, master slave architecture in multi programming and the use of additional sensors to increase accuracy and environmental awareness.

VIII. REFERENCES

1 Arduino, “Arduino Uno Rev3 Documentation.” Online. Available: https://www.arduino.cc/en/Main/ArduinoBoardUno

2 Arduino, “Arduino Language Reference.” Online. Available: https://www.arduino.cc/reference/en/

3 Espressif Systems, “ESP8266 Documentation.” Online. Available: https://www.espressif.com/en/products/socs/esp8266