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Modular, Resilient, and Scalable System Design Approaches -- Lessons learned in the years after DARPA Subterranean Challenge

Prasanna Sriganesh, James Maier, Adam Johnson, Burhanuddin Shirose, Rohan Chandrasekar, Charles Noren, Joshua Spisak, Ryan Darnley, Bhaskar Vundurthy, Matthew Travers

TL;DR

This work addresses the cognitive and coordination challenges of field robotics by proposing a modular, interoperable multi-robot architecture that supports sliding autonomy and adaptive operator interfaces. The system integrates a host discovery service, a central command interface, behavior trees with a mux, and modular navigation and perception services to enable rapid deployment of heterogeneous robot teams. Key contributions include a unified framework for multi-operator, multi-robot control, convoy-style coordination, and system-wide services that promote resilience and extensibility. The approach aims to reduce operator workload while enabling scalable, reliable autonomy in complex, communication-constrained environments, with practical relevance for real-world search-and-rescue deployments.

Abstract

Field robotics applications, such as search and rescue, involve robots operating in large, unknown areas. These environments present unique challenges that compound the difficulties faced by a robot operator. The use of multi-robot teams, assisted by carefully designed autonomy, help reduce operator workload and allow the operator to effectively coordinate robot capabilities. In this work, we present a system architecture designed to optimize both robot autonomy and the operator experience in multi-robot scenarios. Drawing on lessons learned from our team's participation in the DARPA SubT Challenge, our architecture emphasizes modularity and interoperability. We empower the operator by allowing for adjustable levels of autonomy ("sliding mode autonomy"). We enhance the operator experience by using intuitive, adaptive interfaces that suggest context-aware actions to simplify control. Finally, we describe how the proposed architecture enables streamlined development of new capabilities for effective deployment of robot autonomy in the field.

Modular, Resilient, and Scalable System Design Approaches -- Lessons learned in the years after DARPA Subterranean Challenge

TL;DR

This work addresses the cognitive and coordination challenges of field robotics by proposing a modular, interoperable multi-robot architecture that supports sliding autonomy and adaptive operator interfaces. The system integrates a host discovery service, a central command interface, behavior trees with a mux, and modular navigation and perception services to enable rapid deployment of heterogeneous robot teams. Key contributions include a unified framework for multi-operator, multi-robot control, convoy-style coordination, and system-wide services that promote resilience and extensibility. The approach aims to reduce operator workload while enabling scalable, reliable autonomy in complex, communication-constrained environments, with practical relevance for real-world search-and-rescue deployments.

Abstract

Field robotics applications, such as search and rescue, involve robots operating in large, unknown areas. These environments present unique challenges that compound the difficulties faced by a robot operator. The use of multi-robot teams, assisted by carefully designed autonomy, help reduce operator workload and allow the operator to effectively coordinate robot capabilities. In this work, we present a system architecture designed to optimize both robot autonomy and the operator experience in multi-robot scenarios. Drawing on lessons learned from our team's participation in the DARPA SubT Challenge, our architecture emphasizes modularity and interoperability. We empower the operator by allowing for adjustable levels of autonomy ("sliding mode autonomy"). We enhance the operator experience by using intuitive, adaptive interfaces that suggest context-aware actions to simplify control. Finally, we describe how the proposed architecture enables streamlined development of new capabilities for effective deployment of robot autonomy in the field.
Paper Structure (12 sections, 7 figures)

This paper contains 12 sections, 7 figures.

Table of Contents

  1. Introduction
  2. Related Work
  3. Lessons Learned
  4. Proposed Architecture
  5. Host discovery service
  6. Command Interface
  7. Behavior Tree and Mux
  8. Operator Interface and GUI
  9. Navigation Layer
  10. Advanced Multi-agent Coordination
  11. System-wide services
  12. Conclusion

Figures (7)

  • Figure 1: A overview of the proposed system architecture
  • Figure 2: Operator Interface: Example of RViz window, and the touch-enabled GUI
  • Figure 3: The left image shows the behavior subtree for the convoy with multiple robots selected, enabling the 'start convoy' action. The right image demonstrates how the GUI dynamically updates based on the changes in the behavior subtree when a follower robot in an active convoy is selected, presenting actions like 'peeloff' and 'stop convoy'.
  • Figure 4: A pictorial representation of the operator setup showing the two screens
  • Figure 5: Simulation of two robots in convoy formation
  • ...and 2 more figures