Sentinel

Product Introduction

1. Definition: Avea Robotics' Sentinel is a high-performance remote teleoperation software platform for controlling physical robots. It functions as a unified, networked control system that enables real-time, low-latency command and data capture from any location worldwide.
2. Core Value Proposition: Sentinel exists to scale Physical AI deployments by providing robotics companies with the most reliable robot control software on the market, ensuring 100% uptime and instant human intervention when autonomous systems fail. Its primary purpose is to bridge the gap between remote operators and physical robotic systems.

Main Features

1. Ultra-Low Latency Real-Time Control: Sentinel enables smooth, precise robot motion control over the internet with latency as low as 10 milliseconds. It achieves this through optimized networking protocols and efficient data serialization, ensuring the operator's commands are transmitted and executed by the robot's joints and end-effectors with minimal delay. This feature is critical for dynamic tasks requiring immediate feedback.
2. Immersive 3D View & Haptic Feedback: The software provides operators with true depth perception from thousands of miles away, creating an immersive teleoperation experience. This is achieved through advanced video processing and 3D rendering of sensor data. Furthermore, it integrates real-time haptic feedback, transmitting force and touch information from the robot's grippers or sensors back to the operator's controls, allowing them to "feel" the remote environment.
3. Multi-Feed HD Streaming & Data Capture: Sentinel supports the simultaneous streaming of up to 6 full HD video feeds without degrading control performance. This multi-view capability is essential for comprehensive situational awareness. The platform also functions as a robust data collection system, capturing robot joint states, camera feeds (RGB), heatmaps, and point clouds, providing high-quality data for training and improving Physical AI models.

Problems Solved

1. Pain Point: Robotics companies face critical downtime and deployment failures when their autonomous robots encounter unhandled situations or software bugs. Sentinel solves this by providing an instant intervention mechanism through reliable remote teleoperation, preventing costly stoppages and maintaining operational continuity.
2. Target Audience: The primary users include Robotics Engineers, Physical AI Researchers, and Operations Managers at robotics companies. Specifically, it serves teams working on humanoid robots, industrial robotic arms, and custom mobile manipulation platforms who need to manage fleets, collect training data, and ensure supervised autonomy.
3. Use Cases: Key scenarios where Sentinel is essential include Data Collection for Machine Learning (capturing expert demonstrations via teleoperation), Real-World Deployment Management (remotely operating and maintaining robots across different geographic sites), and Supervised Autonomy (monitoring an autonomous process and taking over control when the AI fails).

Unique Advantages

1. Differentiation: Unlike traditional, high-latency remote desktop solutions or proprietary, closed-loop systems, Sentinel is a hardware-agnostic, unified platform. It is designed for seamless integration with a wide variety of robotic architectures (6-DoF, 7-DoF, Humanoid) and provides a single interface for control, data capture, and deployment, drastically reducing integration complexity compared to building custom teleoperation stacks.
2. Key Innovation: The core innovation is the combination of ultra-low latency control with a secure, Docker-containerized deployment model. This allows for a secure, end-to-end encrypted pipeline that can be quickly deployed on-premise or in the cloud. The software's ability to handle custom robot URDFs and joint control APIs while providing a consistent operator experience is a significant technical achievement.

Frequently Asked Questions (FAQ)

1. What is the latency for robot teleoperation with Sentinel? Sentinel is engineered for ultra-low latency robot control, achieving motion-to-video latencies as low as 10 milliseconds. This performance enables precise, real-time manipulation tasks even when operators are continents away from the physical robot.
2. How does Sentinel collect data for training Physical AI? The platform acts as a comprehensive data capture system, automatically recording robot joint states, camera feeds, and point clouds during teleoperation sessions. This high-fidelity data, including RGB and heatmap streams, is crucial for training and validating robotic manipulation and perception models.
3. Is Sentinel secure for controlling robots remotely over the internet? Yes, security is a fundamental design principle. Sentinel ensures end-to-end encryption for all video and control data streams. Furthermore, operational data is collected and stored locally by default, giving companies full control over their proprietary information.
4. Can Sentinel be used with custom or unsupported robotic hardware? Yes, Sentinel is built for flexibility. While it supports a growing list of standard platforms (6-DoF, 7-DoF, Humanoid), it can integrate with custom robots. Users can provide their robot's URDF and joint control API, and the Sentinel team works to establish a connection for a tailored deployment.
5. What is the deployment process for integrating Sentinel with my robots? The deployment follows a streamlined, three-step process: 1) Try a Demo to experience remote teleoperation firsthand, 2) Integrate by sharing your robot's architecture (URDF, API), and 3) Go Live by pulling and running the Sentinel Docker container. Ongoing training and support are provided.