Problem statement
Designing a maze-solving robot for 2024 poses several challenges, including
advanced navigation, real-time decision-making, and integration of cutting-edge
technologies.
Abstract
The maze-solving robot, a type of micro mouse, is intended to navigate and
solve a maze autonomously. Unlike traditional maze-solving robots, the 2024 version
aims to incorporate state-of-the-art technologies to enhance its efficiency and
adaptability. The robot must be able to decode the maze layout independently, make
real-time decisions, and efficiently navigate through the maze to find the optimal path.
Outcome
Sensor Integration:
● Implement advanced sensors such as LiDAR, ultrasonic sensors, and infrared
sensors for precise environment mapping and obstacle detection.
● Utilize a high-resolution camera for visual recognition to enhance the robot’s
ability to interpret maze patterns.
Edge Computing:
● Integrate edge computing capabilities to process sensor data in real-time,
enabling quick decision-making without relying on external computing resources.
Machine Learning Algorithms:
● Train machine learning algorithms to enable the robot to learn and adapt to
different maze configurations.
● Implement reinforcement learning for the robot to make informed decisions based
on its previous experiences.
Autonomous Decision-Making:
● Develop an autonomous decision-making system that allows the robot to
dynamically adjust its path based on real-time sensor feedback.
● Prioritize efficient path planning algorithms to ensure the robot can navigate
through the maze optimally.
Wireless Communication:
● Integrate wireless communication modules for remote monitoring and control of
the robot.
● Implement communication protocols to allow the robot to share data with other
robots, enabling collaborative maze-solving if multiple robots are deployed.
Energy Efficiency:
● Optimize the robot’s power management system to ensure longer operational
time without the need for frequent recharging or battery replacement.
The final outcome is a highly advanced maze-solving robot that can independently
analyze, navigate, and adapt to various maze configurations using cutting-edge
technologies, ultimately demonstrating enhanced performance and efficiency compared
to its predecessors.