For my Master's thesis research, I worked on applying Reinforcement Learning models to real-time Dynamic Scene Graphs (DSGs) on hardware. This builds up on my senior thesis research where I worked on adapting the RL stack to accept DSGs provided by Hydra (a real-time Spatial Perception Engine) as input, and evaluated in simulation. My research aimed to test the accuracy of the RL models while running them on DSGs produced by a real-time SPIN on hardware. I also investigated how to reduce both the computational demands of generating DSGs and the latency of inference for this pipeline such that inference can run in real time.