1,721,022 research outputs found
Safety in human-multi robot collaborative scenarios: a trajectory scaling approach
No full textIn this paper, a strategy to handle the human safety in a multi-robot scenario is devised. In the presented framework, it is foreseen that robots are in charge of performing any cooperative manipulation task which is parameterized by a proper task function. The devised architecture answers to the increasing demand of strict cooperation between humans and robots, since it equips a general multi-robot cell with the feature of making robots and human working together. The human safety is properly handled by defining a safety index which depends both on the relative position and velocity of the human operator and robots. Then, the multi-robot task trajectory is properly scaled in order to ensure that the human safety never falls below a given threshold which can be set in worst conditions according to a minimum allowed distance. Simulations results are presented in order to prove the effectiveness of the approach
A Distributed Framework for Integrated Task Allocation and Safe Coordination in Networked Multi-robot Systems
No full textDeploying a team of autonomous robots, operating collaboratively towards a common objective within dynamic environments, has the potential to improve the system efficiency across several fields. This paper proposes a distributed comprehensive framework enabling a networked multi-robot system to serve time-varying requests arising from different locations within the environment in a distributed and safe manner, i.e., by guaranteeing no collisions with possible obstacles and preserving connectivity among the robots. To this aim, a two-layer architecture is proposed where the top layer is in charge of distributively assigning new service requests to the robots by resorting to an auction-based algorithm, while the bottom layer is in charge of safely navigating the environment to serve the assigned requests by relying on Control Barrier Functions. However, the presence of connectivity constraints might affect the number of service requests that the multi-robot system can handle simultaneously and might lead to deadlock situations where robots cannot reach the designated locations due to loss of network connectivity. Hence, a distributed strategy based on consensus algorithms to detect and solve deadlocks in a distributed fashion is proposed. The completeness of the approach is proved. Simulation results in an agricultural setting and real-world laboratory experiments are provided to validate the effectiveness of the proposed approach
Selective Trimmed Average: A Resilient Federated Learning Algorithm With Deterministic Guarantees on the Optimality Approximation
Full text linkThe federated learning (FL) paradigm aims to distribute the computational burden of the training process among several computation units, usually called agents or workers, while preserving private local training datasets. This is generally achieved by resorting to a server-worker architecture where agents iteratively update local models and communicate local parameters to a server that aggregates and returns them to the agents. However, the presence of adversarial agents, which may intentionally exchange malicious parameters or may have corrupted local datasets, can jeopardize the FL process. Therefore, we propose selective trimmed average (SETA), which is a resilient algorithm to cope with the undesirable effects of a number of misbehaving agents in the global model. SETA is based on properly filtering and combining the exchanged parameters. We mathematically prove that the proposed algorithm is resilient against data and local model poisoning attacks. Most resilient methods presented so far in the literature assume that a trusted server is in hand. In contrast, our algorithm works both in server-worker and shared memory architectures, where the latter excludes the necessity of a trusted server. The theoretical findings are corroborated through numerical results on MNIST dataset and on multiclass weather dataset (MWD)
A finite-time distributed dynamic consensus protocol for tracking maximum (minimum) reference signals
No full textTracking the maximum or minimum of a set of signals is a fundamental task in multiple applications involving coordinated multi-agent systems. This work tackles the dynamic maximum or minimum consensus problem in networked multi-agent systems. Within this framework, every agent has access to a local exogenous signal, and the objective is to ensure that all agents track the time-varying maximum (minimum) signal of the exogenous signals by only relying on local information. We present a novel distributed protocol achieving this objective in finite time under undirected switching network topologies. The assumptions in our study pertain solely to the connectivity of the network topologies and the knowledge of the bounds on the derivatives of the exogenous signals. Numerical results with sinusoidal and piecewise linear signals corroborate the theoretical findings
Distributed Finite-Time Supremum/Infimum Dynamic Consensus Under Directed Network Topology
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Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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