Autonomous loading robots for truck docks—no integration required
Slip Robotics builds physical robots that auto-load and auto-unload truck trailers in under 5 minutes, eliminating the dock wait-time bottleneck. The tech stack—Python, C++, ROS/ROS 2, PyTorch, TensorFlow, Gazebo, Isaac Sim, and industrial protocols (Modbus, EtherNet/IP)—reveals a company balancing simulation-driven development with real-world deployment. Heavy hiring in mid-to-senior engineering alongside active projects in sensor fusion, path planning, and sim-to-real validation suggests they're scaling perception and autonomy capabilities while managing the operational friction of field deployment.
Slip Robotics manufactures and operates autonomous loading robots (SlipBots) that work at any dock, any trailer, with no dock modifications or IT integration. The business runs as a robots-as-a-service network, deploying units into 24/7 manufacturing and logistics operations. Founded in 2020 and based in Atlanta with 51–200 employees, the company is hiring across engineering, manufacturing, and operations in the United States and Mexico. Projects span hardware cargo-handling features, fleet monitoring, sensor fusion, and simulation validation. Current operational priorities include reducing downtime, achieving SLA compliance, and narrowing the gap between simulation and field performance.
Core robotics: Python, C++, ROS, ROS 2, Gazebo, Isaac Sim. ML: PyTorch, TensorFlow. Industrial: Modbus, EtherNet/IP, Fanuc, ABB, KUKA, Universal Robots. Cloud/data: AWS, PostgreSQL, DynamoDB, Snowflake, dbt. Web: React, Node.js, TypeScript.
Hardware cargo-handling features, sensor fusion for multi-modal perception, path planning and obstacle avoidance, simulation model validation, proactive fleet monitoring, and dataset creation for perception model training.
Slip Robotics's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.