TEAMBOTICA is a research environment for the exploration of theories, designs and implementations of team-based robotics.
"A bioterrorism alert is recieved in a dense urban environment. A team of autonomous air and ground vehicles is dispatched. The team enters the environment, assesses the situation and collaboratively coordinates its activity. A biosensor detects toxic gases, the team dynamically positions itself to map out the plume of gas and follow its progress."

A new software capability for the reprogrammable, coordinated command and control of teams of autonomous unmanned air and ground vehicles (UAVs/UGVs) based on an integrated planning and distributed control architecture in which collective behavior is uniquely adaptive and fault tolerant. This work extends the Multi-level agent architecture (MLAA) developed under a previous ONR contract.
The key research objectives are to develop and demonstrate :
  • Interaction methods through which the mission planning level within the MLAA can negotiate with the networking layer, trading mission-level requirements for suggested network resource allocations and expected networking constraints for supporting robot localizations
  • A decision-theoretic approach in which desirabilities/utilities  are assigned to objectives relative to localization, navigation and mission constraints on a robot's choice of task
  • Probabilistic methods for projecting the current state in the context of prevailing constraints and a team's uncertain information about the current situation

Tangible Benefits of TEAMBOTICA

  • An adaptive, robust architecture for collaborative agents
  • Collaborative perception-based localization
  • Vision-based algorithms to support remote positioning
  • Negotiation protocols to support collaboration across multiple dimensions (e.g. communication, localization and mission)
  • Temporal projection to assess the impact of an action at different levels of abstraction
  • A general framework for execution monitoring