Journal of Robotics

Biologically Inspired Robotics 2016


Lead Editor

1Beijing Institute of Technology, Beijing, China

2American University in Cairo, Cairo, Egypt

3Kagawa University, Takamatsu, Japan

4University of Essex, Colchester, UK

Biologically Inspired Robotics 2016


The evolution of robotics has enabled today’s robots to operate in a variety of unstructured and dynamically changing environments in addition to traditional structured environments. Intelligent robots will soon be ready to serve in our home, hospital, office, and outdoors. One key approach to the development of such intelligent and autonomous robots draws inspiration from behavior demonstration of biological systems.

In fact, using this approach, a number of new application areas have recently received significant interests in the robotics community, including service robots, medical robots, education robots, and entertainment robots. It is clear that bioinspired methods are becoming increasingly important in the face of the complexity of today’s demanding applications. Biological inspiration in robotics is leading to complex structures with sensory-motor coordination, in which learning often plays an important role in achieving adaptation. This special issue will focus on the theoretical and technological challenges of evolutionary transformation from biological systems to intelligent robots. All aspects of biologically inspired robots are welcome.

Potential topics include but are not limited to the following:

  • Robotics, mobile robots, aerial robots, and underwater robots
  • Biomimetics, biologically inspired robots, climbing robots, snake robots, and walking robots
  • Automation, control systems, simulation techniques, and control applications
  • Sensor design, multisensor data fusion, and wireless sensor networks
  • MEMS, nanotechnology, NEMS, and micro/nanosystems
  • Telerobotics, human-robot interaction, and human computer interaction
  • Medical robotics and biomedical and rehabilitation engineering
  • Multirobot systems and distributed robotics
  • Computer vision and image processing
Journal of Robotics
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Acceptance rate16%
Submission to final decision109 days
Acceptance to publication21 days
Journal Citation Indicator0.360
Impact Factor1.8
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