7,079 research outputs found
Human management of a robotic swarm
This paper proposes a management algorithm that allows a human operator to organize a robotic swarm via a robot leader. When the operator requests a robot to become a leader, nearby robots suspend their activities. The operator can then request a count of the robots, and assign them into subgroups, one for each task. Once the operator releases the leader, the robots perform the tasks they were assigned to. We report a series of experiments conducted with up to 30 e-puck mobile robots. On average, the counting and allocation algorithm correctly assigns 95 % of the robots in the swarm. The time to count the number of robots increases, on average, linearly with the number of robots, provided they are arranged in random formation
Spatio-Temporal Patterns act as Computational Mechanisms governing Emergent behavior in Robotic Swarms
open access articleOur goal is to control a robotic swarm without removing its swarm-like nature. In other words, we aim to intrinsically control a robotic swarm emergent behavior. Past attempts at governing robotic swarms or their selfcoordinating emergent behavior, has proven ineffective, largely due to the swarm’s inherent randomness (making it difficult to predict) and utter simplicity (they lack a leader, any kind of centralized control, long-range communication, global knowledge, complex internal models and only operate on a couple of basic, reactive rules). The main problem is that emergent phenomena itself is not fully understood, despite being at the forefront of current research. Research into 1D and 2D Cellular Automata has uncovered a hidden computational layer which bridges the micromacro gap (i.e., how individual behaviors at the micro-level influence the global behaviors on the macro-level). We hypothesize that there also lie embedded computational mechanisms at the heart of a robotic swarm’s emergent behavior. To test this theory, we proceeded to simulate robotic swarms (represented as both particles and dynamic networks) and then designed local rules to induce various types of intelligent, emergent behaviors (as well as designing genetic algorithms to evolve robotic swarms with emergent behaviors). Finally, we analysed these robotic swarms and successfully confirmed our hypothesis; analyzing their developments and interactions over time revealed various forms of embedded spatiotemporal patterns which store, propagate and parallel process information across the swarm according to some internal, collision-based logic (solving the mystery of how simple robots are able to self-coordinate and allow global behaviors to emerge across the swarm)
Safe, Remote-Access Swarm Robotics Research on the Robotarium
This paper describes the development of the Robotarium -- a remotely
accessible, multi-robot research facility. The impetus behind the Robotarium is
that multi-robot testbeds constitute an integral and essential part of the
multi-agent research cycle, yet they are expensive, complex, and time-consuming
to develop, operate, and maintain. These resource constraints, in turn, limit
access for large groups of researchers and students, which is what the
Robotarium is remedying by providing users with remote access to a
state-of-the-art multi-robot test facility. This paper details the design and
operation of the Robotarium as well as connects these to the particular
considerations one must take when making complex hardware remotely accessible.
In particular, safety must be built in already at the design phase without
overly constraining which coordinated control programs the users can upload and
execute, which calls for minimally invasive safety routines with provable
performance guarantees.Comment: 13 pages, 7 figures, 3 code samples, 72 reference
Mixed Initiative Systems for Human-Swarm Interaction: Opportunities and Challenges
Human-swarm interaction (HSI) involves a number of human factors impacting
human behaviour throughout the interaction. As the technologies used within HSI
advance, it is more tempting to increase the level of swarm autonomy within the
interaction to reduce the workload on humans. Yet, the prospective negative
effects of high levels of autonomy on human situational awareness can hinder
this process. Flexible autonomy aims at trading-off these effects by changing
the level of autonomy within the interaction when required; with
mixed-initiatives combining human preferences and automation's recommendations
to select an appropriate level of autonomy at a certain point of time. However,
the effective implementation of mixed-initiative systems raises fundamental
questions on how to combine human preferences and automation recommendations,
how to realise the selected level of autonomy, and what the future impacts on
the cognitive states of a human are. We explore open challenges that hamper the
process of developing effective flexible autonomy. We then highlight the
potential benefits of using system modelling techniques in HSI by illustrating
how they provide HSI designers with an opportunity to evaluate different
strategies for assessing the state of the mission and for adapting the level of
autonomy within the interaction to maximise mission success metrics.Comment: Author version, accepted at the 2018 IEEE Annual Systems Modelling
Conference, Canberra, Australi
Blockchain Solutions for Multi-Agent Robotic Systems: Related Work and Open Questions
The possibilities of decentralization and immutability make blockchain
probably one of the most breakthrough and promising technological innovations
in recent years. This paper presents an overview, analysis, and classification
of possible blockchain solutions for practical tasks facing multi-agent robotic
systems. The paper discusses blockchain-based applications that demonstrate how
distributed ledger can be used to extend the existing number of research
platforms and libraries for multi-agent robotic systems.Comment: 5 pages, FRUCT-2019 conference pape
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