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Found 11 papers, 1 papers with code
Robustness of Decentralised Learning to Nodes and Data Disruption
Through these configurations, we are able to show the non-trivial interplay between the properties of the network connecting nodes, the persistence of knowledge acquired collectively before disruption or lack thereof, and the effect of data availability pre- and post-disruption.
DELTA: Decomposed Efficient Long-Term Robot Task Planning using Large Language Models
Recent advancements in Large Language Models (LLMs) have sparked a revolution across various research fields.
Impact of network topology on the performance of Decentralized Federated Learning
We highlight the challenges in transferring knowledge from peripheral to central nodes, attributed to a dilution effect during model aggregation.
Exploring the Impact of Disrupted Peer-to-Peer Communications on Fully Decentralized Learning in Disaster Scenarios
Thus, fully decentralized learning can help in this case.
The effect of network topologies on fully decentralized learning: a preliminary investigation
Specifically, we highlight the different roles in this process of more or less connected nodes (hubs and leaves), as well as that of macroscopic network properties (primarily, degree distribution and modularity).
Predicting Dense and Context-aware Cost Maps for Semantic Robot Navigation
The preliminary experiments suggest that the cost maps generated by our network are suitable for the MPC and can guide the agent to the semantic goal more efficiently than a baseline approach.
Learning Occupancy Priors of Human Motion from Semantic Maps of Urban Environments
Understanding and anticipating human activity is an important capability for intelligent systems in mobile robotics, autonomous driving, and video surveillance.
Autonomous Driving
Robotics
A Feedback Scheme to Reorder a Multi-Agent Execution Schedule by Persistently Optimizing a Switchable Action Dependency Graph
A common mitigation approach is to re-solve the MAPF using the current, delayed AGV positions.
Experimental Comparison of Global Motion Planning Algorithms for Wheeled Mobile Robots
Planning smooth and energy-efficient motions for wheeled mobile robots is a central task for applications ranging from autonomous driving to service and intralogistic robotics.
Human Motion Trajectory Prediction: A Survey
With growing numbers of intelligent autonomous systems in human environments, the ability of such systems to perceive, understand and anticipate human behavior becomes increasingly important.
A Fast Randomized Method to Find Homotopy Classes for Socially-Aware Navigation
We introduce and show preliminary results of a fast randomized method that finds a set of K paths lying in distinct homotopy classes.
