EDBT 2026 Demo / reviewers in the wild / expert
Matthew J. Doyle
dblp:181/4263
· DBLP profile ↗
3ranked-venue papers
2as first author
1since 2021 · last 2021
0000-0002-2349-8433ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2 · 1 first-authorSystems, architecture and hardware · 2 · 1 first-authorApplied, interdisciplinary, general and emerging computing · 1 · 1 first-author · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Artificial intelligence
2 papers |
Multi-agent systems · 44% Motion planning and robot control · 29% Legged, aerial and field robots · 19% |
Topics — the 5 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Motion planning and robot control › multi-robot control
decentralized control |
0.5 | 1 | 2021 | Modular Fluidic Propulsion Robots · IEEE Trans. Robotics 2021 |
Knowledge, reasoning and agents › Multi-agent systems
modular robotics |
0.5 | 1 | 2021 | Modular Fluidic Propulsion Robots · IEEE Trans. Robotics 2021 |
Knowledge, reasoning and agents › Multi-agent systems › multi-agent control
distributed motion control |
0.2 | 1 | 2016 | Modular Hydraulic Propulsion: A robot that moves by routing fluid through itself · ICRA 2016 |
Robotics › Legged, aerial and field robots › mobile robot locomotion
modular robot locomotion |
0.2 | 1 | 2016 | Modular Hydraulic Propulsion: A robot that moves by routing fluid through itself · ICRA 2016 |
Robotics › Robot manipulation › actuator design
soft actuation |
0.1 | 1 | 2021 | Modular Fluidic Propulsion Robots · IEEE Trans. Robotics 2021 |
Methods — techniques the papers use, named apart from their topics
decentralized control · 0.8pneumatic propulsion · 0.5hydraulic propulsion · 0.53d simulation · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | Modular Fluidic Propulsion RobotsabstractWe propose a novel concept for modular robots, termed modular fluidic propulsion (MFP), which promises to combine effective propulsion, a large reconfiguration space, and a scalable design. MFP robots are modular fluid networks. To propel, they route fluid through themselves. In this article, both hydraulic and pneumatic implementations are considered. The robots move towards a goal by way of a decentralized controller that runs independently on each module face, uses two bits of sensory information and requires neither run-time memory, nor communication. We prove that 2-D MFP robots reach the goal when of orthogonally convex shape, or reach a morphology-dependent distance from it when of arbitrary shape. We present a 2-D hydraulic MFP prototype and show, experimentally, that it succeeds in reaching the goal in at least 90% of trials, and that 71% less energy is expended when modules can communicate. Moreover, in simulations with 3-D hydraulic MFP robots, the decentralized controller performs almost as well as a state-of-the-art and centralized controller. Given the simplicity of the hardware requirements, the MFP concept could pave the way for modular robots to be used at sub-centimeter-scale, where effective modular propulsion systems have not been demonstrated. Matthew J. Doyle, João V. Amorim Marques, Isaac Vandermeulen, Christopher Parrott, Andreas Kolling, Roderich Groß |
IEEE Trans. Robotics | 1 |
| 2019 | Decentralized Pose Control of Modular Reconfigurable Robots Operating in Liquid EnvironmentsabstractModular reconfigurable robots are touted for their flexibility, as their bodies can assume a wide range of shapes. A particular challenge is to make them move efficiently in 3D without compromising the scalability of the system. This paper proposes decentralized and fully reactive controllers for pose control of 3D modular reconfigurable robots. The robots operate in liquid environments, and move by routing fluid through themselves. Each module uses only two bits of sensory information per face. Additionally, the modules can use up to five bits of information that are exchanged via shared power lines. We prove that robots of convex shape are guaranteed to reach a goal object with a preferred orientation. Using computer simulations of Modular Hydraulic Propulsion robots, all controllers are assessed for different environments, system sizes and noise, and their performances compared against a centralized controller. Given the simplicity of the solutions, modules could be realized at scales below a millimeter-cube, where robots of high spatial resolution could perform accurate movements in 3D liquid environments. João V. Amorim Marques, Anil Özdemir, Matthew J. Doyle, Daniela Rus, Roderich Groß |
IROS | 3 |
| 2016 | Modular Hydraulic Propulsion: A robot that moves by routing fluid through itselfabstractThis paper introduces the concept of Modular Hydraulic Propulsion, in which a modular robot that operates in a fluid environment moves by routing the fluid through itself. The robot's modules represent sections of a hydraulics network. Each module can move fluid between any of its faces. The modules (network sections) can be rearranged into arbitrary topologies. We propose a decentralized motion controller, which does not require modules to communicate, compute, nor store information during run-time. We use 3-D simulations to compare the performance of this controller to that of a centralized controller with full knowledge of the task. We also detail the design and fabrication of six 2-D prototype modules, which float in a water tank. Results of systematic experiments show that the decentralized controller, despite its simplicity, reliably steers modular robots towards a light source. Modular Hydraulic Propulsion could offer new solutions to problems requiring reconfigurable systems to move precisely in 3-D, such as inspection of pipes, vascular systems or other confined spaces. Matthew J. Doyle, Fernando Perez-Diaz, Christopher Parrott, Roderich Groß |
ICRA | 1 |