ROBOTICS AND AUTONOMOUS SYSTEMS

Scope & Guideline

Leading the Charge in Robotics and Automated Technologies.

Introduction

Welcome to the ROBOTICS AND AUTONOMOUS SYSTEMS information hub, where our guidelines provide a wealth of knowledge about the journal’s focus and academic contributions. This page includes an extensive look at the aims and scope of ROBOTICS AND AUTONOMOUS SYSTEMS, highlighting trending and emerging areas of study. We also examine declining topics to offer insight into academic interest shifts. Our curated list of highly cited topics and recent publications is part of our effort to guide scholars, using these guidelines to stay ahead in their research endeavors.
LanguageEnglish
ISSN0921-8890
PublisherELSEVIER
Support Open AccessNo
CountryNetherlands
TypeJournal
Convergefrom 1988 to 2024
AbbreviationROBOT AUTON SYST / Robot. Auton. Syst.
Frequency12 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
AddressRADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS

Aims and Scopes

The journal 'Robotics and Autonomous Systems' focuses on the advancement of robotic technologies and autonomous systems, aiming to disseminate significant research findings and methodologies that contribute to the field. The journal encompasses a broad range of topics related to robotics, combining theoretical approaches with practical applications.
  1. Robotic Manipulation and Control:
    Research on the development of advanced control strategies for robotic systems, including manipulation, trajectory tracking, and interaction with dynamic environments.
  2. Autonomous Navigation and Path Planning:
    Studies focusing on algorithms and techniques for enabling autonomous robots to navigate complex environments, including multi-agent systems and obstacle avoidance.
  3. Human-Robot Interaction:
    Exploration of methodologies for enhancing interactions between humans and robots, including collaborative tasks, user-centered design, and social robotics.
  4. Reinforcement Learning and AI in Robotics:
    Application of machine learning techniques, particularly reinforcement learning, to improve robotic decision-making, skill acquisition, and adaptability.
  5. Robotics in Specialized Applications:
    Research addressing specific applications of robotics, such as healthcare, agriculture, and disaster response, highlighting the practical implications of robotic technologies.
  6. Sensor Fusion and Perception Systems:
    Innovations in integrating various sensors to enhance robot perception, enabling better environmental understanding and interaction.
  7. Swarm Robotics and Multi-Robot Systems:
    Investigation into cooperative behaviors and task allocation strategies for groups of robots, emphasizing decentralized control and communication.
The journal has observed several emerging themes that indicate the evolving landscape of robotics research. These trends reflect the integration of advanced technologies and methodologies that are shaping the future of the field.
  1. Deep Learning and Neural Networks:
    An increasing number of studies are leveraging deep learning techniques for various robotic applications, including perception, control, and decision-making, emphasizing the transformative role of AI in robotics.
  2. Adaptive and Intelligent Robotics:
    Research focusing on adaptive systems that can learn and adjust to changing environments and tasks is on the rise, showcasing the movement towards more intelligent and autonomous robots.
  3. Robotics in Healthcare:
    There is a growing emphasis on the application of robotics in healthcare settings, particularly in rehabilitation and assistive technologies, driven by the need for innovative solutions in patient care.
  4. Collaborative Robotics (Cobots):
    The rise of collaborative robots designed to work alongside humans in various settings is gaining traction, highlighting the importance of safety and efficiency in human-robot collaboration.
  5. Robotics for Environmental Monitoring:
    Emerging research is focusing on the use of robotics for environmental applications, such as precision agriculture and disaster response, reflecting a commitment to addressing global challenges.
  6. Multi-Agent Systems and Swarm Intelligence:
    There is a notable increase in research related to multi-agent systems and swarm robotics, emphasizing collective behaviors and decentralized control for complex tasks.

Declining or Waning

While the journal continues to explore a wide array of topics, certain areas of research are becoming less prominent in recent publications. This decline may reflect shifting interests in the field or advancements that have made some methodologies less relevant.
  1. Traditional Robotics Techniques:
    As the field advances, traditional control methods and simple robotic designs are becoming less emphasized in favor of more complex, adaptive systems that utilize AI and machine learning.
  2. Static Path Planning Approaches:
    There is a noticeable reduction in focus on conventional path planning methods that do not account for dynamic environments, with a shift towards more adaptive and predictive techniques.
  3. Basic Sensor Technologies:
    Research centered on basic sensor technologies is declining as more sophisticated and integrated sensor systems are being developed, leading to an increased focus on sensor fusion and advanced perception.
  4. Manual Programming of Robots:
    The trend is moving away from manual programming techniques towards more automated and intelligent systems that rely on learning from demonstrations and user interactions.
  5. Low-Level Control Systems:
    There is a diminishing interest in low-level control systems that do not incorporate higher-level decision-making processes, as the focus shifts towards more holistic, intelligent approaches.

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