Simulation is only as good as its approximation to the real world… its ‘equivalence’. We’ve been exploring how intelligent simulation with a modular framework can deliver results faster to drive autonomous system development.
The world is experiencing significant progress in AI-enabled autonomous mobile systems. Could autonomous mobile robots navigating dynamic environments open up new automation opportunities for industry?
To decentralise, or not to decentralise, that is the question. This Web3 dilemma reflects the likely thoughts of current digital leaders who want to make the best use of their digital assets while maintaining trust in their data systems.
The rate adoption of automation and autonomous systems in non-manufacturing segments is growing faster. AMR’s (Automated Mobile Robots) are working alongside people in warehouses and helping in improving productivity. But is this enough?
They are already physically loading our online shopping baskets, vacuuming our homes and maintaining our lawns. But what will it take for automated and autonomous systems to proliferate across industry and society – on the roads, city streets, building sites, fields, factories and schools?
It’s a common fallacy that perfecting navigation for robots and autonomous vehicles is straightforward. Actually, it’s a tough nut to crack. But our robot navigation algorithm could unlock a range of industrial automation applications.