Autonomous Wingman

We are seeking a highly skilled software developer to design and build a wingman software stack that will serve as the foundation for an autonomous wingman system. The stack will run on Jetson Xavier NX or Orin NX, integrating advanced computer vision, AI-based decision-making, and flight control capabilities. This role involves developing, integrating, and testing key software components, ensuring robust performance in simulation and real-world applications.
Key Responsibilities:
• Develop decision trees as a baseline for future decision-based logic.
• Design and implement a high-performance video processing pipeline using GStreamer/DeepStream, enabling 4K video processing at 30fps.
• Build an AI-powered object detection pipeline, running an optimized artificial neural network (ANN) on a full-resolution 4K video feed at a minimum of 30fps.
• Implement a state-of-the-art video tracking algorithm, enabling automatic and manual tracking of detected objects. Implement business logic for user-engaged tracking.
• Implement a video stabilization algorithm to enhance image stability within the processing pipeline.
• Enable multi-source video streaming, supporting different frame rates, resolutions and formats.
• Modify the PX4 stack to enable autonomous flight in follow mode, tracking targets obtained from the video tracker. Customize the PID loop to fit platform requirements.
• Integrate the WINGMAN software stack with GAZEBO simulation, ensuring functionality in a controlled test environment.
• Integrate the WINGMAN software stack with Qground control to enable control, status and video streaming.
• Conduct on-site software integration and testing, verifying real-world performance.
• Support field testing, ensuring seamless system operation in practical scenarios.
Qualifications & Experience:
• Expertise in C, C++, and Python for software development and optimization.
• Experience with GStreamer and DeepStream for real-time video processing.
• Strong knowledge of artificial neural networks (ANN) and convolutional neural networks (CNN) for object detection.
• Hands-on experience with PX4 flight controllers and UAV system integration.
• Proficiency in Gazebo simulation for testing autonomous flight algorithms.
• Background in image processing, tracking algorithms, and video stabilization.
• Ability to work on field testing and real-world software integration.
• Strong problem-solving skills and a passion for developing autonomous systems.
Preferred Skills:
• Knowledge of CUDA programming for GPU-accelerated computing.
• Experience with parallel processing and optimization for AI applications.
• Familiarity with MAVLink protocol for UAV communication.