Future Ideas & Exploration
Exploring the intersection of autonomous systems, detection technologies, and counter-measures. Technical concepts in early research phase.
The idea is to explore whether principles from distributed fault detection can translate to mobile aerial platforms. In grid monitoring, robustness often comes from having many simple, low-cost nodes rather than relying on a few complex ones. Swarm-based inverter coordination works similarly, with stability emerging from collective behavior rather than centralized control. I'm curious whether the same approach could apply to infrastructure inspection, using fleets of minimal UAVs that collectively cover large areas, tolerate individual failures, and perform local processing instead of streaming everything back to a base station.
This would involve building both the aerial platforms and the ground systems needed to coordinate them. Working on both sides at once seems useful because each informs the other.
Platform Development
The goal here is to design small UAV platforms with limited onboard computation and tight power budgets, capable of performing basic anomaly detection locally rather than depending on constant connectivity. The focus would be on platforms that are individually simple and maybe not perfectly reliable, but that work well enough as a group. Losing one node shouldn't break the system. The hope is that simple local rules, when applied across many vehicles operating over transmission lines or substations, can produce useful collective behavior without requiring each unit to be particularly sophisticated.
Coordination and Observation Infrastructure
On the ground side, the goal is to build systems that can track multiple vehicles, coordinate their movements in environments where GPS or radio signals may not be reliable (which is common near power infrastructure), and piece together distributed observations into something coherent. This setup would also make it possible to study how failures spread through a distributed aerial network and how different coordination strategies affect overall resilience.
Why This Interests Me
The underlying question feels familiar from my work on network monitoring systems for power grids: how do you build distributed systems that stay reliable when the individual pieces are cheap, low power, and likely to fail eventually? Adding aerial platforms introduces mobility and new sensing possibilities, but the core challenge seems similar. Achieving robustness through coordination rather than through perfecting each component is something I'd like to understand better, and this seems like a good way to explore it.
Key Technical Areas
Building various unmanned aerial platforms to understand flight dynamics, control systems, and autonomous behavior.
Focus Areas:
- •Flight control algorithms and stabilization
- •Autonomous navigation and path planning
- •Communication systems and telemetry
- •Power management and propulsion efficiency
- •Payload integration and sensor mounting
Vision-based detection and tracking using cameras and image processing to identify and follow aerial targets.
Focus Areas:
- •Computer vision and object detection algorithms
- •Multi-camera tracking and triangulation
- •Motion prediction and trajectory estimation
- •Day/night operation and lighting conditions
- •Real-time processing and low-latency response
Radio frequency monitoring and analysis to detect control signals, telemetry, and communication patterns.
Focus Areas:
- •Signal detection and classification
- •Direction finding and source localization
- •Frequency spectrum analysis
- •Protocol identification and decoding
- •Multi-sensor fusion for improved accuracy
Research into methods for disrupting, disabling, or neutralizing unauthorized UAV operations in controlled environments.
Focus Areas:
- •Signal jamming and communication disruption
- •GPS spoofing and navigation interference
- •Physical interception methods
- •Directed energy concepts
- •Effectiveness testing and countermeasure resistance
The research follows an iterative cycle where improvements on one side inform developments on the other, creating a continuous learning loop:
Build & Test
Develop UAV platform with specific characteristics and test in controlled environment
Detect & Analyze
Attempt detection using various methods, identify weaknesses and signature patterns
Improve & Iterate
Apply learnings to both platforms and detection systems, repeat cycle with improvements
Note: All research and testing will be conducted in compliance with local regulations, in controlled environments, and with proper safety protocols. The goal is educational understanding of system capabilities and limitations.
Following the Journey
These ideas are in early research phase. As work progresses, updates will be documented in the Lab section and eventually become full projects.