NRN Robotics Roadmap

NRN’s approach to robotic sports is grounded in progressive, real-world experimentation. Our roadmap is structured into phases, each designed to validate and evolve the capabilities of our Sim-to-Real reinforcement learning (RL) pipeline. From robotic arms to humanoids and racing drones, we aim to demonstrate the full range of embodied AI in competitive settings.

Phase 1: Concept Validation & Pipeline Robustness

In this initial phase, we focus on showcasing the integrity of our RL-powered continuous learning pipeline using a robotic arm named RME-1 (pronounced “Arm-y 1”). This stage is centered around proving core capabilities like data collection and real-time learning. Demonstrations will include:

• Object pickup and manipulation tasks

• Stacking and fine motor control

• Mini-putt challenges to showcase an understanding of environmental physics

• Dynamic sparring drills to highlight reaction time and motion prediction

These tests serve as the foundation for more complex embodied AI behavior and validate our client-side data collection tools and training infrastructure in real-world conditions.

Phase 2: Diversifying Sport Primitives

Robotic Combat

Building on the success of RME-1, we will apply the full NRN RL pipeline to humanoid agents.

• Begin with miniature humanoid robots to test RL agent performance in bipedal combat

• Launch a full robotic combat competition campaign featuring humanoid tournaments

• Scale toward larger, more complex humanoids with expanded mobility and dexterity

• Long-term milestone: Develop and deploy full-sized humanoid competitors trained via continual learning, capable of dynamic physical interaction in competitive matches

Robotic Racing & Athletics

In addition to robotic combat, we will expand the NRN platform to other categories of robotic competition, each emphasizing different skill domains and control systems:

• Robot Dog Racing & Challenges: Quadrupedal agents showcasing agility and terrain adaptation

• Robot Kart Racing: Fast-paced, agent-controlled vehicles navigating real tracks

• Drone Racing: Aerial agents trained on trajectory prediction and reactive flight control

• Robot Athletics: Obstacle courses, climbing, jumps—pushing physical versatility and sim-to-real transfer