The first navigation benchmark that evaluates robots by profit per run. CostNav bridges the gap between impressive research demos and sustainable businesses by modeling the complete economic lifecycle of delivery robots.
WoRV (World Models for Robotics and Vehicle Control) Team has been pioneering VLA-based RFM (Robotic Foundation Models) for agricultural, logistics, defense, construction, and manufacturing domains since 2021.
We go beyond "fancy lab research." We operate in the real world with a fleet of hundreds of robots replacing human labor in industrial sites. This allows us to collect robust training data, establish new research hypotheses daily, and immediately evaluate and realign our models through field deployment and business feedback.
We offer the optimal environment to "pre-train" for the upcoming era of Physical AI.
A unified evaluation harness for Vision-Language-Action models — accepted at the ICRA 2026 Workshop on From Data to Decisions.
View on GitHub arXiv View LeaderboardEconomic-Aware Navigation Benchmark for Autonomous Delivery Robots
The first navigation benchmark that evaluates robots by profit per run. CostNav bridges the gap between impressive research demos and sustainable businesses by modeling the complete economic lifecycle of delivery robots.
Scaling Vision-Action Pretraining on Desktop Data for Transfer to Embodied AI
Leveraging large-scale desktop data to pre-train vision-action models, demonstrating effective transfer to embodied robotic tasks.
Interactive Autoregressive 3D Gaming Worlds with Camera Pose as a Unifying Geometric Representation
A generative world model that builds interactive 3D worlds from gameplay data, using camera pose as a unifying geometric representation. A collaboration between KAIST CVLab, Adobe Research, and WoRV @ Maum.ai.
Commonsense-Aware Navigation System for Intuitive Human-Robot Interaction
A novel navigation system that interprets user sketches to guide robots, bridging the gap between human intuition and robot control.
Join a team of top-tier talents tackling the hardest problems in Physical AI.
We promise industry-leading compensation, alternative military service options, and the most reliable colleagues.