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 …
Socially aware robot navigation system in human-populated and interactive environments based on an adaptive spatial density function and space affordances
Traditionally robots are mostly known by society due to the wide use of manipulators, which
are generally placed in controlled environments such as factories. However, with the …
are generally placed in controlled environments such as factories. However, with the …
Learning human-aware path planning with fully convolutional networks
N Pérez-Higueras, F Caballero… - 2018 IEEE international …, 2018 - ieeexplore.ieee.org
This work presents an approach to learn path planning for robot social navigation by
demonstration. We make use of Fully Convolutional Neural Networks (FCNs) to learn from …
demonstration. We make use of Fully Convolutional Neural Networks (FCNs) to learn from …
Teaching robot navigation behaviors to optimal RRT planners
This work presents an approach for learning navigation behaviors for robots using Optimal
Rapidly-exploring Random Trees (RRT^*∗) as the main planner. A new learning algorithm …
Rapidly-exploring Random Trees (RRT^*∗) as the main planner. A new learning algorithm …
Prediction of reward functions for deep reinforcement learning via Gaussian process regression
J Lim, S Ha, J Choi - IEEE/ASME Transactions on Mechatronics, 2020 - ieeexplore.ieee.org
Inverse reinforcement learning (IRL) is a technique for automatic reward acquisition,
however, it is difficult to apply to high-dimensional problems with unknown dynamics. This …
however, it is difficult to apply to high-dimensional problems with unknown dynamics. This …
Scene context-aware rapidly-exploring random trees for global path planning
T Hirakawa, T Yamashita… - 2019 IEEE International …, 2019 - ieeexplore.ieee.org
This paper introduces a global path planning method for autonomous systems. Global path
planning finds a feasible and collision-free path in an environment in which various kinds of …
planning finds a feasible and collision-free path in an environment in which various kinds of …
NRTIRL Based NN-RRT* Path Planner in Human-Robot Interaction Environment
Y Wang, Y Kong, Z Ding, W Chi, L Sun - International Conference on …, 2022 - Springer
In human-robot interaction environment, it is of great significance for mobile robots to have
the awareness of social rules, to realize the socialization and anthropomorphism of robot …
the awareness of social rules, to realize the socialization and anthropomorphism of robot …
Reducing the planning horizon through reinforcement learning
Planning is a computationally expensive process, which can limit the reactivity of
autonomous agents. Planning problems are usually solved in isolation, independently of …
autonomous agents. Planning problems are usually solved in isolation, independently of …
基于群体智能成果的路径规划程序自动生成系统
王雨倩， 丁嵘 - 智能科学与技术学报, 2022 - infocomm-journal.com
路径规划算法被广泛地应用于各种运动规划任务, 如机器人运动, 自动驾驶等. 迄今为止,
许多优秀的路径规划算法被提出并被应用于不同领域. 对于一个特定的任务环境 …
许多优秀的路径规划算法被提出并被应用于不同领域. 对于一个特定的任务环境 …
Socially Adaptive Path Planning Based on Generative Adversarial Network
Y Wang, Y Kong, W Chi, L Sun - arXiv preprint arXiv:2404.18687, 2024 - arxiv.org
The natural interaction between robots and pedestrians in the process of autonomous
navigation is crucial for the intelligent development of mobile robots, which requires robots …
navigation is crucial for the intelligent development of mobile robots, which requires robots …