Deep reinforcement learning in mobile robotics - a concise review

被引:0
|
作者
Prasuna, Rayadurga Gnana [1 ]
Potturu, Sudharsana Rao [1 ]
机构
[1] Koneru Lakshmaiah Educ Fdn, Dept Elect & Commun Engn, Hyderabad 500075, Telangana, India
关键词
Mobile robotics; Deep Reinforcement Learning; Challenges; Autonomous robots Survey; END-TO-END; COLLISION-AVOIDANCE; VISUAL NAVIGATION; ENVIRONMENTS; PERCEPTION; NETWORKS; SEARCH;
D O I
10.1007/s11042-024-18152-9
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Mobile robotics is one of the emerging research area in the robotics. The recently evolving techniques, artificial intelligence and precise hardware controller design gave new scope in the area of mobile robots. Initially, deep learning (DL) approach is used for operating robotics with this approach robots can be operated in fixed pattern. Later to perform autonomous operations researchers used deep reinforcement learning (DRL) approach. This DRL approach transformed the face of robotics from conventional point to more precise, modern and self-control robots. This literature review gives the information about different approaches and developments in the area of robotics using deep reinforcement learning. Furthermore, this paper gives the information about different algorithms to deal with robotics. Moreover, this paper discusses about the different sensors and their importance. Moreover, this paper gives the information about developments and the challenges in robotics using deep reinforcement learning.
引用
收藏
页码:70815 / 70836
页数:22
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