A deep reinforcement learning approach to optimal morphologies generation in reconfigurable tiling robots
Reconfigurable robots have the potential to perform complex tasks by adapting their
morphology to different environments. However, designing optimal morphologies for these …
morphology to different environments. However, designing optimal morphologies for these …
Reinforcement learning based, staircase negotiation learning: Simulation and transfer to reality for articulated tracked robots
A Mitriakov, P Papadakis, J Kerdreux… - IEEE Robotics & …, 2021 - ieeexplore.ieee.org
Autonomous control of reconfigurable robots is crucial for their deployment in diverse
environments. However, its development is hampered by the diversity of hardware and task …
environments. However, its development is hampered by the diversity of hardware and task …
Deep Reinforcement Learning for Flipper Control of Tracked Robots in Urban Rescuing Environments
Tracked robots equipped with flippers and LiDAR sensors have been widely used in urban
search and rescue. Achieving autonomous flipper control is important in enhancing the …
search and rescue. Achieving autonomous flipper control is important in enhancing the …
Autonomous state-based flipper control for articulated tracked robots in urban environments
T Azayev, K Zimmermann - IEEE Robotics and Automation …, 2022 - ieeexplore.ieee.org
We demonstrate a hybrid approach to autonomous flipper control, focusing on a fusion of
hard-coded and learned knowledge. The result is a sample-efficient and modifiable control …
hard-coded and learned knowledge. The result is a sample-efficient and modifiable control …
Deep reinforcement learning for flipper control of tracked robots
The autonomous control of flippers plays an important role in enhancing the intelligent
operation of tracked robots within complex environments. While existing methods mainly rely …
operation of tracked robots within complex environments. While existing methods mainly rely …
An autonomous stair climbing method for the crawler robot based on a hybrid reinforcement learning controller
S Zhang, J Wang, E Wang, Y Sun - Neurocomputing, 2024 - Elsevier
In response to problems in using deep reinforcement learning to perform the stair climbing
task for the crawler robot, such as the lack of theoretical values for stair size range, the …
task for the crawler robot, such as the lack of theoretical values for stair size range, the …
An open-source software framework for reinforcement learning-based control of tracked robots in simulated indoor environments
A Mitriakov, P Papadakis, S Garlatti - Advanced Robotics, 2022 - Taylor & Francis
A simulation framework based on the open-source robotic software Gazebo and the Robot
Operating System is presented for articulated tracked robots, designed for reinforcement …
Operating System is presented for articulated tracked robots, designed for reinforcement …
Robots Learn Increasingly Complex Tasks with Intrinsic Motivation and Automatic Curriculum Learning: Domain Knowledge by Emergence of Affordances …
Multi-task learning by robots poses the challenge of the domain knowledge: complexity of
tasks, complexity of the actions required, relationship between tasks for transfer learning. We …
tasks, complexity of the actions required, relationship between tasks for transfer learning. We …
基于深度强化学习的履带机器人摆臂控制方法
潘海南， 陈柏良， 黄开宏， 任君凯， 程创… - 系统仿真 …, 2024 - china-simulation.com
摆臂式履带机器人具有一定的地形适应能力, 实现摆臂的自主控制对提升机器人在复杂环境中的
智能化作业水平具有重要意义. 结合专家越障知识和技术指标对机器人的摆臂控制问题进行马尔 …
智能化作业水平具有重要意义. 结合专家越障知识和技术指标对机器人的摆臂控制问题进行马尔 …
Staircase negotiation learning for articulated tracked robots with varying degrees of freedom
A Mitriakov, P Papadakis… - 2020 IEEE International …, 2020 - ieeexplore.ieee.org
Tracked robots capable of negotiating 3D terrains require delicate control, most often
tailored to a specific platform or setting. For staircase traversal in particular, autonomous …
tailored to a specific platform or setting. For staircase traversal in particular, autonomous …