RGo Robotics
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About
RGo Robotics provides a comprehensive AI-powered perception platform designed to grant mobile machines human-level understanding of their surroundings. The system leverages advanced computer vision and sensor fusion to enable autonomous mobile robots (AMRs), automated guided vehicles (AGVs), and drones to navigate complex, dynamic environments with high reliability. By providing machines with location-aware intelligence, the platform allows them to see and understand the physical world, facilitating a shift from simple automation to truly intelligent autonomy. This technology is primarily delivered through the RGo Perception Engine, which can be embedded during the manufacturing process or retrofitted onto existing hardware. The technology stack is built on Physical AI, which translates real-world physical data into actionable digital information in real-time. A standout feature of the suite is the Intelligent Mapping solution, which utilizes NVIDIA Isaac Perceptor acceleration libraries. This specific tool drastically accelerates the site commissioning process, turning what used to be a months-long deployment into a matter of weeks. The platform also includes modules for Intelligent Autonomy and Intelligent Site monitoring, creating a unified information platform that serves as a critical enabler for large-scale AI automation across various industries. This solution is ideal for robotics manufacturers and industrial operators in sectors such as logistics, manufacturing, and facility management. It is particularly beneficial for those looking to deploy robots in environments where traditional navigation methods struggle, such as areas with high human traffic or changing layouts like hospitals, hotels, and warehouses. By using state-of-the-art AI algorithms, RGo enables these machines to learn on-the-go and adapt to their surroundings without extensive manual programming or environmental modification. What differentiates RGo Robotics from competitors is its focus on the economics of deployment and its collaboration with major technology partners like NVIDIA, Qualcomm, and Arm. While many perception systems focus solely on navigation, RGo's platform emphasizes reducing the time-to-value for end-users by simplifying the mapping and setup phases. The integration of its Perception Engine with edge computing capabilities ensures that robots can process complex environmental data locally, maintaining high performance and safety standards without relying on constant cloud connectivity.
Pros & Cons
Reduces site commissioning time from months to weeks using AI-powered mapping.
Integrates with industry-standard hardware from NVIDIA, Arm, and Qualcomm.
Supports both indoor and outdoor logistics for seamless transitions between environments.
Enables robots to learn and adapt to their surroundings in real-time using on-the-go learning.
Applicable to a wide range of machines including AMRs, AGVs, and UAVs.
Pricing information is not publicly available and requires contacting sales.
Specific hardware requirements for the Perception Engine are not fully detailed on the site.
Full implementation may require collaboration with the RGo expert team for custom integration.
Use Cases
Warehouse managers can deploy fleets of autonomous mobile robots faster by reducing site commissioning from months to weeks.
Robotics manufacturers can integrate the Perception Engine into their machines to provide human-level awareness for complex environments.
Facility managers in hospitals or hotels can utilize retrofitted cleaning robots that safely navigate around guests and staff.
Logistics operators can use the platform to bridge the gap between indoor and outdoor transport with a single navigation solution.
Security firms can power surveillance machines with real-time scene understanding to improve threat detection and site monitoring.
Platform
Task
Features
• sensor fusion technology
• retrofittable perception hardware
• on-the-go learning
• real-time scene understanding
• human-level perception
• physical ai information platform
• intelligent mapping
• perception engine platform
FAQs
What is the main benefit of RGo’s Intelligent Mapping solution?
The Intelligent Mapping solution significantly reduces the complexity and cost of site commissioning for mobile robots. It can transform a deployment process that typically takes months into one that takes only a few weeks.
Can the RGo Perception Engine be added to existing robots?
Yes, the platform is designed to be flexible and can be embedded during the manufacturing phase or retrofitted onto existing machines. This allows operators to upgrade their current fleet with AI-powered perception capabilities.
Which industries can benefit from RGo Robotics technology?
The technology is suitable for a wide range of applications including logistics, manufacturing, cleaning, delivery, and security. It is currently used in environments like warehouses, hotels, hospitals, and even residential homes.
How does RGo's technology handle complex or changing environments?
RGo uses state-of-the-art computer vision and AI algorithms that allow machines to learn on-the-go. This enables them to perceive their surroundings in real-time and adapt to dynamic changes without manual intervention.
What hardware platforms are compatible with RGo's solutions?
RGo collaborates with major technology providers and its Perception Engine is integrated with platforms from NVIDIA, Qualcomm, and Arm. This ensures high performance on edge computing hardware designed for robotics.
Pricing Plans
Custom
Unknown Price• Perception Engine platform
• Intelligent Mapping solution
• NVIDIA Isaac Perceptor integration
• Support for indoor and outdoor logistics
• Site commissioning acceleration
• Real-time Physical AI info
• Human-level perception
• On-the-go learning
Job Opportunities
Senior Software Engineer
Empower mobile robots with human-level perception and intelligent mapping to reduce deployment time from months to weeks in complex logistics and industrial sites.
Education Requirements:
B.Sc. or higher in computer science or similar from a university
Experience Requirements:
5+ years of relevant experience
Other Requirements:
Skilled at implementing scalable software through the use of design patterns in modern C++
Highly proficient in C++ and software design
Able to work across the software and system stack
Able to perform fast prototyping, including hardware, software & apps
Comfortable debugging complex systems
Responsibilities:
Early design & architecture
Component integration
Bring-up
Middleware/frameworks
Algorithm integration
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