Autonomous Navigation Robot

Problem Statement

Indoor autonomous navigation needs robust mapping, localization and planning in unknown environments.

Objectives

• - Implement SLAM-capable mobile robot
• - Fuse LiDAR, encoder and IMU with EKF
• - Perform autonomous planning and obstacle avoidance
• - Build ROS-based prototype

Methodology

The project follows a structured implementation approach that includes 2D LiDAR GMapping with ROS, EKF-based localization stack, Global and local navigation planners, and Simulation plus real environment validation. These steps are executed iteratively to validate assumptions, improve performance, and ensure reliable delivery of the final solution.

Expected Outcome

By the end of this project, the team is expected to deliver Unknown-space mapping, Accurate fused localization, and Reliable autonomous obstacle avoidance. Together, these outcomes reflect both technical feasibility and practical value for demos, evaluation, and future scaling.

Future Scope

• - 3D sensing and dynamic replanning
• - Multi-robot coordination
• - Warehouse and delivery deployment

Components and Budget