Real-Time Innovations (RTI) has launched the latest version of its framework software, which is designed to address the development and deployment challenges faced by companies building remotely-operated autonomous systems.
Connext 6.1 introduces features to enable real-time remote operation over any network. The company said if the network connection changes as the system moves, “connectivity is seamless without reconnecting, secure without renegotiating, and reliable without losing information”. This enables remote operations to continue in real time without interruption.
Furthermore, Connext 6.1 supports and optimises fast communications across LAN and WAN networks. RTI added its solution does not require software changes to support diverse network types.
According to RTI, its API abstracts the underlying networks, allowing developers to target any environment offering the first practical design for control of remote autonomous systems.
“To empower innovation and accelerate value delivery to our global customers, we are developing a mining technology ecosystem supported by a platform on RTI Connext DDS,” said Anthony Reid, director of platforms and applications at Komatsu.
“With RTI Connext DDS, we’re able to connect data from all different types of machines, mining processes, systems, and third-party applications while leveraging edge and cloud computing to enable interoperability, autonomy, and optimisation. The Real-Time WAN Transport and Cloud Discovery Service in Connext 6.1 help us to overcome technical hurdles while simplifying our software architecture.”
Additionally, the cloud discovery service simplifies deployment of dynamic systems in which applications, assets, and their network addresses may not be known at configuration time.
It provides a means for applications to discover each other and directly communicate, peer-to-peer. This minimises latency and maximises throughput. RTI added this is far superior to traditional centralised broker solutions.
The built-in data compression is designed to improves efficiency over bandwidth-constrained networks. Compression maximises bandwidth use, lowering overhead and latency while increasing throughput. A choice of compression algorithms and levels allows optimisation of processor versus network utilisation for different payload types.
