Robotic Systems Portfolio

Flagship projects translating research into deployable autonomy.

From swarm robotics testbeds to mission-ready navigation frameworks and assistive platforms, each project couples rigorous experimentation with real-world validation.

Explore by Focus

Filter by research focus to surface relevant results. Each card links to source code, publications, and demonstrations where available.

FormicaBot: Bio-inspired Swarm Robotics Platform

Principal Researcher  |  BIT Robotics Lab  |  2024–Present

Holistic framework closing the simulation-to-reality gap in swarm robotics through biological validation and hardware-software co-design.

  • Dual-modality virtual pheromone system (optical/thermal) for resilient communication
  • Stochastic PDE modeling of ant foraging under environmental stressors
  • Edge-AI pipeline with quantized MobileNetV3 for decentralized target recognition
  • Bio-inspired hexapedal locomotion achieving ≤1.2W power consumption

Outcomes: 89% foraging efficiency in complex navigation • Patent pending • Publications in Nature Reviews Bioengineering and Sensors.

Robust Navigation Framework for GPS-Denied Environments

Lead Developer  |  BIT Navigation Lab  |  2023–Present

Autonomy stack delivering resilient localization and planning under sensor degradation and environmental uncertainty.

  • Multi-modal sensor fusion (LiDAR-IMU-Vision) with Extended Kalman Filter
  • Bio-inspired Ant Colony Optimization integrated with deep Q-learning
  • ROS 2 and Gazebo simulation with realistic perturbation modeling
  • Real-time SLAM and motion planning in dynamic environments

Performance: Validated in cluttered indoor/outdoor environments • Robust to sensor failure.

Smart Wheelchair & Cloud-Assistive System

System Architect  |  BIT Assistive Robotics  |  2024–Present

IoT-enabled assistive platform integrating real-time telemetry, adaptive control interfaces, and cloud analytics.

  • Cloud-connected platform capturing high-frequency telemetry streams
  • Adaptive control interfaces tailored for heterogeneous user capabilities
  • Predictive analytics for preventive maintenance and utilization insights
  • Secure REST APIs enabling remote assistance workflows

Impact: Enhances independence for mobility-impaired users • Scalable monitoring for healthcare providers.

Aerospace Sensor Systems & Reliability Analysis

Research Contributor  |  Multi-institutional Collaboration  |  2021–2023

Wearable monitoring and reliability evaluation frameworks for aerospace applications focused on mission assurance.

  • Sensor fusion algorithms for cognitive workload assessment
  • Performance degradation modeling for aerospace engine diagnostics
  • Reliability framework recognized with IEEE IATMSI Best Paper Award
  • Multi-institutional publications in aerospace engineering journals

Deployment Metrics

Quantifiable performance indicators captured across simulation, lab validation, and field trials.

89%

Foraging efficiency in adversarial swarm trials

≤1.2 W

Average power draw for hexapedal locomotion

4+

Integrated sensing modalities per navigation stack

IEEE

Best Paper Award for reliability framework

Bring resilience to your field deployments.

Collaborative projects welcome across swarm robotics, autonomous navigation, and assistive technology. Reach out via email to initiate a technical deep dive.