[HTML][HTML] Multi-agent deep reinforcement learning for multi-robot applications: A survey
J Orr, A Dutta - Sensors, 2023 - mdpi.com
Deep reinforcement learning has produced many success stories in recent years. Some
example fields in which these successes have taken place include mathematics, games …
example fields in which these successes have taken place include mathematics, games …
A review of mobile robot motion planning methods: from classical motion planning workflows to reinforcement learning-based architectures
Motion planning is critical to realize the autonomous operation of mobile robots. As the
complexity and randomness of robot application scenarios increase, the planning capability …
complexity and randomness of robot application scenarios increase, the planning capability …
Hierarchical multi-robot navigation and formation in unknown environments via deep reinforcement learning and distributed optimization
L Chang, L Shan, W Zhang, Y Dai - Robotics and Computer-Integrated …, 2023 - Elsevier
Compared with a single robot, Multi-robot Systems (MRSs) can undertake more challenging
tasks in complex scenarios benefiting from the increased transportation capacity and fault …
tasks in complex scenarios benefiting from the increased transportation capacity and fault …
A survey of learning‐based robot motion planning
A fundamental task in robotics is to plan collision‐free motions among a set of obstacles.
Recently, learning‐based motion‐planning methods have shown significant advantages in …
Recently, learning‐based motion‐planning methods have shown significant advantages in …
[HTML][HTML] Autodrive: A comprehensive, flexible and integrated digital twin ecosystem for autonomous driving research & education
Prototyping and validating hardware–software components, sub-systems and systems within
the intelligent transportation system-of-systems framework requires a modular yet flexible …
the intelligent transportation system-of-systems framework requires a modular yet flexible …
Robust behavioral cloning for autonomous vehicles using end-to-end imitation learning
In this work, we present a lightweight pipeline for robust behavioral cloning of a human
driver using end-to-end imitation learning. The proposed pipeline was employed to train and …
driver using end-to-end imitation learning. The proposed pipeline was employed to train and …
Hierarchical reinforcement learning with opponent modeling for distributed multi-agent cooperation
Many real-world applications can be formulated as multi-agent cooperation problems, such
as network packet routing and coordination of autonomous vehicles. The emergence of …
as network packet routing and coordination of autonomous vehicles. The emergence of …
Machine learning based relative orbit transfer for swarm spacecraft motion planning
In this paper we describe a machine learning based framework for spacecraft swarm
trajectory planning. In par-ticular, we focus on coordinating motions of multi-spacecraft in …
trajectory planning. In par-ticular, we focus on coordinating motions of multi-spacecraft in …
[HTML][HTML] Study of variational inference for flexible distributed probabilistic robotics
By combining stochastic variational inference with message passing algorithms, we show
how to solve the highly complex problem of navigation and avoidance in distributed multi …
how to solve the highly complex problem of navigation and avoidance in distributed multi …
AutoDRIVE: A Comprehensive, Flexible and Integrated Digital Twin Ecosystem for Enhancing Autonomous Driving Research and Education
Prototyping and validating hardware-software components, sub-systems and systems within
the intelligent transportation system-of-systems framework requires a modular yet flexible …
the intelligent transportation system-of-systems framework requires a modular yet flexible …