Human Machine Teaming - Enabling Framework (702953450) - Re-opening 1

THIS ADVERT IS AN OPPORTUNITY FOR PARTICIPANTS TO JOIN THE EXTANT HMT FRAMEWORK ORIGINALLY RELEASED QUARTER 2 2022 (REFERENCE: 702953450). IF YOU ARE ALREADY A PARTICIPANT WITHIN THIS FRAMEWORK YOU DO NOT NEED TO COMPLETE THIS PROCESS. THIS PQQ/ITT PROCESS IS FOR NEW ENTRANTS TO THE FRAMEWORK ONLY. The Human Machine Teaming (HMT) programme collates current lessons from Army's experimentation activity in Robotic and Autonomous Systems (RAS), and enable rapid iterations, across the full stack of potential capabilities, across a 3-year programme. This will ensure the necessary stability, time and opportunity to generate sufficient evidence to inform future cost/benefit analysis activity and balance of investment decisions. HMT is being delivered through a multi supplier Framework Agreement, which is segregated into LOTS. This manages and delivers the continued development and maturation of capabilities and requirements in RAS in accordance with the Strategy outlined in the 'British Army's Approach to RAS'. This is required to build on the Transformation Fund experimentation completed within the Robotic Platoon Vehicle (RPV), Nano Unmanned Air Systems (nUAS) and Theseus Projects, along with associated learning from Army Warfighting Experiment (AWE) to create operational advantage for land forces, by integrating adaptable RAS within Human Machine Teams, to generate mass and tempo whilst reducing risk. The framework has a 3 year duration (2.5 years remaining), and is valued at £300M. This programme of work is being delivered by the Expeditionary Robotics Centre of Expertise (ERCoE) using the Future Capability Group's (FCG) novel Buy and Try at Scale Operational(BATSO) commercial model, with sufficient framework headroom, to complete iterative spiral development of technological solutions. Framework participation will be subject to successfully completing a Pre Qualification Questionnaire (PQQ) and Invitation toTender (ITT) process. This will commence with the publication of the PQQ for Human Machine Teaming through the DSP.