Case Studies

Advanced Autonomous Robotics for Defense R&D

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Delivering Mission-Ready Navigation in
GPS-Denied Environments

Field-Testing Reduction
0 %
Deployment Acceleration
0 %

Client Profile:

Our client is a premier government research organization operating under the Ministry of Defence, Government of
India. Based in Bengaluru, this strategic R&D institution specializes in advanced robotics, autonomous systems,
and underwater defense technologies. With a highly skilled workforce of 500+ scientists and engineers, it drives
cutting-edge innovations for national security applications, including unmanned platforms, AI-enabled systems,
and secure communication solutions.

Problem Statement

The client faced critical gaps in deploying autonomous systems for defense applications:

Localization Failure:

Inability to maintain accurate positioning indoors/outdoors without GPS signals, risking mission integrity.

Sensor Fusion Complexity:

Unreliable real-time integration of LiDAR, IMU, and stereo camera data, causing navigation drift.

Software Capability Gap:

Limited in-house expertise to develop scalable ROS2-based autonomy stacks for path planning and 3D mapping.

Validation Bottlenecks:

Absence of Hardware-in-the-Loop Simulation (HILS) delayed algorithm testing, escalating field deployment risks.

Accelerated Timelines:

Stringent 12-month deadline to meet Ministry of Defence milestones amid resource constraints.

Our Solution:

MicroGenesis delivered a modular autonomous navigation stack with end-to-end capabilities:

Core Technical Architecture

ROS2 Foxy Navigation Stack:

- Unified framework integrating real-time localization, 3D mapping, path planning, and mission control nodes.
- Seamless sensor fusion for LiDAR, IMU, stereo camera, and GPS.

Validation Infrastructure:

Hardware-in-the-Loop Simulation (HILS): Gazebo/ROS2 framework emulating underwater conditions, enabling 80% pre-deployment validation.

Precision Localization Engine:

- LiDAR-Inertial SLAM: Generated real-time 3D maps with <5 cm drift and 12-DOF altitude data.
- EKF-Based Fusion: Combined IMU, GPS, and LiDAR inputs for continuous drift compensation in GPS-denied zones.

Accelerated Timelines:

Stringent 12-month deadline to meet Ministry of Defence milestones amid resource constraints.

Development Approach

Phase
Activities
Tools/Outputs
Development
Custom ROS2 nodes for SLAM, EKF, path planning
C++, Python, Nav2 Stack
Testing
HILS validation of obstacle navigation
Gazebo, RViz, Ubuntu 20.04
Deployment
Docker packaging; on-premises integration
Docker, GitLab CI/CD
Knowledge Transfer
SDD/ICD documentation; on-site training
Technical manuals, simulation reports

Business Impact:

The solution delivered mission-ready autonomy within 12 months, achieving quantifiable outcomes:

Performance Metrics

KPI
Result
Operational Impact
Operational Impact
<5 cm drift in GPS-denied environments
Reliable navigation in critical zones
Testing Efficiency
80% validation via HILS pre-deployment
40% reduction in on-site testing time
Deployment Speed
Dockerized configuration
30% faster integration
Project Timeline Compliance
On-time delivery within 12 months
Met MoD defense milestones

Strategic Advantages

Future-Ready Architecture:

Modular design enables AI-based semantic mapping and swarm coordination upgrades.

Client Autonomy:

Comprehensive documentation/training empowered in-house team ownership

Tactical Demonstration:

Successfully validated autonomous multi-floor transitions with dynamic obstacle avoidance.