Robotics Skill Challenge - Maze Solver

The Maze Solver Challenge is a hands-on autonomous robotics competition designed to evaluate participants’ algorithmic thinking, sensor integration, and real-time decision-making through intelligent maze navigation tasks. The challenge focuses on building robots that can independently analyze a structured maze, detect paths, avoid dead ends, and reach the target point with maximum efficiency and accuracy. Robots must process sensor data, execute embedded navigation logic, and dynamically adapt their movement strategies to handle turns, junctions, and blocked paths. The event emphasizes optimization, reliability, and intelligent decision-making under time-bound and performance-driven conditions. Together, these objectives provide a competitive platform for students to demonstrate technical expertise, problem-solving skills, and applied knowledge in robotics, automation, and embedded intelligence systems. Event Focus: Hands-on autonomous robotics competition based on intelligent maze navigation Focus on sensor integration, navigation algorithms, and embedded programming Real-time decision-making and performance-based evaluation Pre-event training and mentorship through structured workshops Platform for showcasing innovation, logic optimization, and technical excellence Event Flow: Phase 1 – Online Registration & Coordination Participants register, receive event guidelines, maze specifications, and complete team onboarding. Phase 2 – Hybrid Pre-Event Program A 2-day hands-on workshop conducted in online and offline modes to prepare teams for the Maze Solver Challenge. Workshop Dates: 5th–6th February 2026 Training Includes: Sensor calibration and obstacle detection techniques Navigation algorithm implementation (wall-following, shortest-path logic, etc.) Motor control and movement precision Embedded coding and system debugging Test runs on sample maze layouts Round 1 – On-Campus Competition Teams design, build, and program their autonomous robots based on the provided maze specifications. Robots are tested in real time on the competition maze, and performance is evaluated based on navigation accuracy, decision-making efficiency, stability, and successful completion of maze sections. Round 2 – Grand Finale Shortlisted teams will present and demonstrate: A fully functional autonomous maze-solving robot Navigation strategy and algorithm explanation Optimization methods for speed, accuracy, and reliability Final performance results and key technical learnings Prize Pool: Maze Solver Challenge 1st Prize: ₹10,000 2nd Prize: ₹5,000 Eligibility: Undergraduate (UG) students Postgraduate (PG) students Research scholars Open to students from all disciplines with an interest in robotics, automation, AI/ML, and embedded systems Why Participate: Gain hands-on exposure to autonomous navigation systems Learn sensor integration and navigation algorithm design Apply problem-solving and optimization techniques in live competition scenarios Receive structured training through pre-event workshops Showcase innovation and technical skills at a national platform Network with mentors, faculty, judges, and fellow innovators Earn recognition through prizes, certificates, and institutional acknowledgment