DCIST CRA – Distributed and Collaborative Intelligent Systems and Technology Collaborative Research Alliance (CRA)

/* DISABLE LAYERSLIDER*/ add_theme_support( 'deactivate_layerslider' ); DCIST CRA – Distributed and Collaborative Intelligent Systems and Technology Collaborative Research Alliance (CRA)

The Distributed and Collaborative Intelligent Systems and Technology Collaborative Research Alliance (CRA) will create Autonomous, Resilient, Cognitive, Heterogeneous Swarms that can enable humans to participate in a wide range of missions in dynamically changing, harsh, and contested environments. These include search and rescue of hostages, information gathering after terrorist attacks or natural disasters, and humanitarian missions.

Swarms of humans and robots will operate as a cohesive team with robots preventing humans from coming in harms way (Force Protection) and extending and amplifying their reach to allow one human to do the work of ten humans (Force Multiplication). Our research will create swarms that will provide on-demand services in these missions.

DCIST graphic

Swarms: DCIST research will develop the methodologies for architecting autonomous, resilient, cognitive, heterogeneous swarms of sensors, robots, and intelligent machines that can work with humans.
Networking: Autonomous networking provides the backbone for perception, control, and learning in teams and is required in all three research areas: Distributed Learning, Heterogeneous Group Control, Adaptive and Resilient Behaviors.
Intelligence: DCIST research will enable a novel class of intelligent agents that are able to learn and adapt to new environments and to other agents in a distributed way, and be adaptive and resilient to sudden changes and threats.
Autonomy: Autonomy in individual agents and groups of agents requires distributed learning and perception, networking across individuals in the groups, and control of heterogeneous groups.
Resilience: DCIST research will address resilience in heterogeneous groups, specifically in the context of changes in the environment, new threats to the team, and disruptions and intrusions in the network.
Collaboration: Collaboration between autonomous agents and with humans requires distributed learning and control of heterogeneous agents, and enables resilience to sudden and catastrophic events.

Technical Thrusts

Abstract network of lines and dots, illustration

Distributed
Intelligence

Heterogeneous
Group Control

Adaptive and Resilient
Behaviors

Cross-Disciplinary
Experimentation

Technical Thrusts

News

Hierarchical Planning for Heterogeneous Multi-Robot Routing Problems via Learned Subteam Performance

CORSAIR: Convolutional Object Retrieval and Symmetry-AIded Registration

Robust multimodal data association

ELLIPSDF: Joint Object Pose and Shape Optimization with a Bi-level Ellipsoid and Signed Distance Function Description

Robust data association in high-outlier regimes

Active Bayesian Multi-class Mapping from Range and Semantic Segmentation Observation

Multi-robot Scheduling for Environmental Monitoring as a Team Orienteering Problem

Optimizing Non-Markovian Information Gain Under Physics-Based Communication Constraints

Active Exploration and Mapping via Iterative Covariance Regulation over Continuous SE(3) Trajectories

An Army Research Laboratory Collaborative Research Alliance