ACHORD: communication-aware multi-robot coordination with intermittent connectivity

© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksCommunication is an important capability for multi-robot exploration because (1) inter-robot communication (comms) improves coverage efficiency and (2) robot-to-base comms improves situational awareness. Exploring comms-restricted (e.g., subterranean) environments requires a multi-robot system to tolerate and anticipate intermittent connectivity, and to carefully consider comms requirements, otherwise mission-critical data may be lost. In this paper, we describe and analyze ACHORD (Autonomous & Collaborative High-Bandwidth Operations with Radio Droppables), a multi-layer networking solution which tightly co-designs the network architecture and high-level decision-making for improved comms. ACHORD provides bandwidth prioritization and timely and reliable data transfer despite intermittent connectivity. Furthermore, it exposes low-layer networking metrics to the application layer to enable robots to autonomously monitor, map, and extend the network via droppable radios, as well as restore connectivity to improve collaborative exploration. We evaluate our solution with respect to the comms performance in several challenging underground environments including the DARPA SubT Finals competition environment. Our findings support the use of data stratification and flow control to improve bandwidth-usage.Peer ReviewedPostprint (author's final draft

Communications-Aware Robotics: Challenges and Opportunities

The use of Unmanned Ground Vehicles (UGVs) and Unmanned Aerial Vehicles (UAVs) has seen significant growth in the research community, industry, and society. Many of these agents are equipped with communication systems that are essential for completing certain tasks successfully. This has led to the emergence of a new interdisciplinary field at the intersection of robotics and communications, which has been further driven by the integration of UAVs into 5G and 6G communication networks. However, one of the main challenges in this research area is how many researchers tend to oversimplify either the robotics or the communications aspects, hindering the full potential of this new interdisciplinary field. In this paper, we present some of the necessary modeling tools for addressing these problems from both a robotics and communications perspective, using the UAV communications relay as an example.Comment: 6 pages, 4 figures, accepted for presentation to the 2023 International Conference on Unmanned Aircraft Systems (ICUAS) at Lazarski University, Warsaw, Polan

Swarm-Based Techniques for Adaptive Navigation Primitives

Adaptive Navigation (AN) has, in the past, been successfully accomplished by using mobile multi-robot systems (MMS) in highly structured formations known as clusters. Such multi-robot adaptive navigation (MAN) allows for real-time reaction to sensor readings and navigation to a goal location not known a priori. This thesis successfully reproduces MAN cluster techniques via swarm control techniques, a less computationally expensive but less formalized control technique for MMS, which achieves robot control through a combination of primitive robot behaviors. While powerful for large numbers of robots, swarm robotics often relies on “emergent” swarm behaviors resulting from robot-level behaviors, rather than top-down specification of swarm behaviors. For adaptive navigation purposes, it was desired to be able to specify swarm-level behavior from a top down perspective rather than experimenting with emergent behaviors. To this end, a simulation environment was developed to allow rapid development and vetting of swarm behaviors while easily interfacing with an existing testbed for validation on hardware. An initial suite of robot primitive and composite behaviors was developed and vetted using this simulator, and the behaviors were validated using the existing testbed in Santa Clara University’s Robotics System Laboratory (RSL). Of particular importance were the adaptive navigation primitives of extrema finding and contour finding and following. These AN primitives were tested over a variety of experimental parameters, yielding design guidelines for top-down specification of swarm robotic adaptive navigation. These design guidelines are presented, and their usefulness is demonstrated for a Contour Finding and Following application using the RSL’s testbed. Finally, possible future work to expand the capability of swarm-based adaptive navigation techniques is discussed

Formal Synthesis of Controllers for Safety-Critical Autonomous Systems: Developments and Challenges

In recent years, formal methods have been extensively used in the design of autonomous systems. By employing mathematically rigorous techniques, formal methods can provide fully automated reasoning processes with provable safety guarantees for complex dynamic systems with intricate interactions between continuous dynamics and discrete logics. This paper provides a comprehensive review of formal controller synthesis techniques for safety-critical autonomous systems. Specifically, we categorize the formal control synthesis problem based on diverse system models, encompassing deterministic, non-deterministic, and stochastic, and various formal safety-critical specifications involving logic, real-time, and real-valued domains. The review covers fundamental formal control synthesis techniques, including abstraction-based approaches and abstraction-free methods. We explore the integration of data-driven synthesis approaches in formal control synthesis. Furthermore, we review formal techniques tailored for multi-agent systems (MAS), with a specific focus on various approaches to address the scalability challenges in large-scale systems. Finally, we discuss some recent trends and highlight research challenges in this area

Multi-robot deployment planning in communication-constrained environments

A lo largo de los últimos años se ha podido observar el aumento del uso de equipos de robots en tareas en las cuales es imposible o poco eficiente la intervención de los humanos, e incluso que implica un cierto grado de riesgo para una persona. Por ejemplo, monitorización de entornos de difícil acceso, como podrían ser túneles, minas, etc. Éste es el tema en el que se ha enfocado el trabajo realizado durante esta tesis: la planificación del despliegue de un equipo de agentes para la monitorización de entornos.La misión de los agentes es alcanzar unas localizaciones de interés y transmitirle la información observada a una estación base estática. Ante la ausencia de una infraestructura de comunicaciones, una transmisión directa a la base es imposible. Por tanto, los agentes se deben coordinar de manera autónoma, de modo que algunos de ellos alcancen los objetivos y otros realicen la función de repetidor para retransmitir la información.Nos hemos centrado en dos líneas de investigación principales, relacionadas con dos maneras del envío de la información a la estación base. En el primer enfoque, los agentes deben mantener un enlace de comunicación con la base en el momento de alcanzar los objetivos. Con el fin de, por ejemplo, poder interactuar desde la base con un robot que ha alcanzado el objetivo. Para ello hemos desarrollado un método que obtiene las posiciones óptimas para los agentes utilizados a modo de repetidor. A continuación, hemos implementado un método de planificación de caminos de modo que los agentes pudiesen navegar el máximo tiempo posible dentro de zonas con señal. Empleando conjuntamente ambos métodos, los agentes extienden el área de cobertura de la estación base, estableciendo un enlace de comunicación desde la misma hasta los objetivos marcados.Utilizando este método, el equipo es capaz de lidiar con variaciones del entorno si la comunicación entre los agentes no se pierde. Sin embargo, los eventos tan comunes e irrelevantes para los seres humanos, como el simple cierre de una puerta, pueden llegar a ser críticos para el equipo de robots. Ya que esto podría interrumpir la comunicación entre el equipo. Por ello, hemos propuesto un método distribuido para que el equipo sea capaz de reconectarse, formando una cadena hacia un objetivo, en escenarios donde haya variaciones con respecto al mapa inicial que poseían los robots.La segunda parte de la presente tesis se ha centrado en misiones de recopilación de datos de un entorno. Aquí la comunicación con la estación base, en el instante de alcanzar un objetivo, no es necesaria y a menudo imposible. Por tanto, en este tipo de escenarios, es más eficiente que algunos agentes, llamados trabajadores, recopilen datos del entorno, y otros, denominados colectores, reúnan la información de los que trabajan para periódicamente retransmitirla a la base. De este modo tan solo los colectores realizan largos viajes a la estación base, mientras que los trabajadores emplean la mayor parte de su tiempo exclusivamente a la recopilación de datos.Primero, hemos desarrollado dos métodos para la planificación de caminos para la sincronización entre los trabajadores y colectores. El primero, muestrea el espacio de manera aleatoria, para obtener una solución lo más rápido posible. El segundo, usando FMM, es más lento, pero obtiene soluciones óptimas.Finalmente, hemos propuesto una técnica global para la misión de recopilación de datos. Este método consiste en: encontrar el mejor balance entre la cantidad de trabajadores y colectores, la mejor división del escenario en áreas de trabajo para los trabajadores, la asociación de los trabajadores para transmitir los datos recopilados a los colectores o directamente a la estación base, así como los caminos de los colectores. El método propuesto trata de encontrar la mejor solución con el fin de entregar la mayor cantidad de datos y que el tiempo de "refresco" de los mismos sea el menor posible.<br /

Multi-vehicle Framework for the Development of Robotic Games: the Marco Polo Case

This thesis presents a multi-vehicle platform and framework for robotics education and research. The framework has been designed primarily as a tool for teaching children about engineering in general and robotics in particular. The framework is composed of a unique combination of hardware components and software libraries that allow users to easily design and implement sophisticated robotics behaviors. Several example games are presented including ``Obstacle Course," ``Scavenger Hunt," ``Robot Jeopardy," and ``Marco Polo." This thesis also introduces ``Marco Polo" as a robotics problem that mimics the pursuit-evasion game often played by children in swimming pools. Specifically, the question of finding an optimal pursuit strategy under the condition of intermittent communication is addressed. Finally, a problem related to ``Marco Polo" involving a multi-agent sensor network optimally placed in an environment for the purpose of detecting and intercepting intruders is presented together with a proposed solution methodology and simulation and experimental results.School of Electrical & Computer Engineerin