Results 241 to 250 of about 5,119,496 (310)
Deep Compressed Communication and Application in Multi-Robot 2D-Lidar SLAM: An Intelligent Huffman Algorithm. [PDF]
Sensors (Basel)Zhang L, Deng J.
europepmc +1 more source
Bio-Inspired Neural Network for Real-Time Evasion of Multi-Robot Systems in Dynamic Environments. [PDF]
Biomimetics (Basel)Li J, Yang SX.
europepmc +1 more source
Multi-Agent Deep Reinforcement Learning for Multi-Robot Applications: A Survey
Sensors, 2023 Deep reinforcement learning has produced many success stories in recent years. Some example fields in which these successes have taken place include mathematics, games, health care, and robotics. In this paper, we are especially interested in multi-agent
AYAN Dutta
exaly +2 more sources
Some of the next articles are maybe not open access.
Related searches:
Related searches:
RoCo: Dialectic Multi-Robot Collaboration with Large Language Models
IEEE International Conference on Robotics and Automation, 2023We propose a novel approach to multi-robot collaboration that harnesses the power of pre-trained large language models (LLMs) for both high-level communication and low-level path planning.
Mandi Zhao, Shreeya Jain, Shuran Song
semanticscholar +1 more source
IEEE Robotics and Automation Letters, 2023
Collaborative Simultaneous Localization And Mapping (C-SLAM) is a vital component for successful multi-robot operations in environments without an external positioning system, such as indoors, underground or underwater.
Pierre-Yves Lajoie, G. Beltrame
semanticscholar +1 more source
Collaborative Simultaneous Localization And Mapping (C-SLAM) is a vital component for successful multi-robot operations in environments without an external positioning system, such as indoors, underground or underwater.
Pierre-Yves Lajoie, G. Beltrame
semanticscholar +1 more source
Scalable Multi-Robot Collaboration with Large Language Models: Centralized or Decentralized Systems?
IEEE International Conference on Robotics and Automation, 2023A flurry of recent work has demonstrated that pre-trained large language models (LLMs) can be effective task planners for a variety of single-robot tasks.
Yongchao Chen +4 more
semanticscholar +1 more source
Collaborative Multi-Robot Search and Rescue: Planning, Coordination, Perception, and Active Vision
IEEE Access, 2020 Search and rescue (SAR) operations can take significant advantage from supporting autonomous or teleoperated robots and multi-robot systems. These can aid in mapping and situational assessment, monitoring and surveillance, establishing communication ...
Tomi Westerlund +2 more
exaly +2 more sources
IEEE Robotics and Automation Letters, 2022
The challenges to solving the collision avoidance problem lie in adaptively choosing optimal robot velocities in complex scenarios full of interactive obstacles.
Ruihua Han +6 more
semanticscholar +1 more source
The challenges to solving the collision avoidance problem lie in adaptively choosing optimal robot velocities in complex scenarios full of interactive obstacles.
Ruihua Han +6 more
semanticscholar +1 more source
M3ED: Multi-Robot, Multi-Sensor, Multi-Environment Event Dataset
2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2023We present M3ED, the first multi-sensor event camera dataset focused on high-speed dynamic motions in robotics applications. M3ED provides high-quality synchronized and labeled data from multiple platforms, including ground vehicles, legged robots, and ...
Kenneth Chaney +8 more
semanticscholar +1 more source
Multi-Robot Cooperative Socially-Aware Navigation Using Multi-Agent Reinforcement Learning
IEEE International Conference on Robotics and Automation, 2023In public spaces shared with humans, ensuring multi-robot systems navigate without collisions while respecting social norms is challenging, particularly with limited communication.
Weizheng Wang +3 more
semanticscholar +1 more source