Get real-time visibility of the status of all your deployments without relying on emails so you are out in front of issues that could affect your customers.
Observing a robotic fleet is not simple, and every company has its own metrics to indicate the overall health of the fleet. InOrbit’s interactive, real-time dashboard can support any level of observation/control. Featuring high-level key performance indicators, slice-and-dice fleet visualization, and drill-down to individual robots, InOrbit’s configurable widgets let you showcase or explore any metrics. Customers can use extensive yet intuitive settings or APIs to adapt the dashboard to their specific needs.
Effective robot operation demands both real-time intervention and the ability to retrospectively review certain situations to analyze incidents. InOrbit offers a simple, powerful interface to reveal and filter captured incidents (and trends) by any criteria. From there you can dive into the specifics of the situation, with the underlying dynamic data front and center for the duration of each incident. In-app notifications, as well as integrations with collaboration platforms, can help notify the right person on incidents.
Leveraging the abundant data from a variety of robot data sources, InOrbit can apply artificial intelligence and machine learning techniques to analyze patterns to generate actionable insights and recommendations that translate into cost savings through efficiencies. This can help companies anticipate problems before they occur.
Autonomous robots are often dispatched to complete specific tasks or missions. In the case of mobile robots, this may involve following paths or moving between predefined locations; cobot arms may be physically interacting or manipulating items around them. InOrbit helps plan these missions, track progress and status, and identify situations where the robot needs extra help to complete its mission.
Scaling a robot fleet requires continuous learning from patterns and edge cases emerging in the field. InOrbit’s agent runs on each robot to optimize data collection, analysis at the edge, and transmission to the cloud for further processing. Leveraging InOrbit’s Adaptive Diagnostics allows the agent to adjust the data sampling rate, resolution and summarization in real time, adapting to specific needs across the fleet.