Biologically Inspired Robotics
Features
- Presents cutting-edge research in biologically inspired robotics and biomimetics
- Highlights research trends and future development of biorobotics and biologically inspired robot design
- Brings together contributions from well-known experts
- Examines the use of micro and nano robots for biomedical applications and cybernetics
- Includes a wealth of illustrations and equations
Summary
Robotic engineering inspired by biology—biomimetics—has many potential applications: robot snakes can be used for rescue operations in disasters, snake-like endoscopes can be used in medical diagnosis, and artificial muscles can replace damaged muscles to recover the motor functions of human limbs. Conversely, the application of robotics technology to our understanding of biological systems and behaviors—biorobotic modeling and analysis—provides unique research opportunities: robotic manipulation technology with optical tweezers can be used to study the cell mechanics of human red blood cells, a surface electromyography sensing system can help us identify the relation between muscle forces and hand movements, and mathematical models of brain circuitry may help us understand how the cerebellum achieves movement control.
Biologically Inspired Robotics contains cutting-edge material—considerably expanded and with additional analysis—from the 2009 IEEE International Conference on Robotics and Biomimetics (ROBIO). These 16 chapters cover both biomimetics and biorobotic modeling/analysis, taking readers through an exploration of biologically inspired robot design and control, micro/nano bio-robotic systems, biological measurement and actuation, and applications of robotics technology to biological problems.
Contributors examine a wide range of topics, including:
- A method for controlling the motion of a robotic snake
- The design of a bionic fitness cycle inspired by the jaguar
- The use of autonomous robotic fish to detect pollution
- A noninvasive brain-activity scanning method using a hybrid sensor
- A rehabilitation system for recovering motor function in human hands after injury
- Human-like robotic eye and head movements in human–machine interactions
A state-of-the-art resource for graduate students and researchers in the fields of control engineering, robotics, and biomedical engineering, this text helps readers understand the technology and principles in this emerging field.
Table of Contents
Introduction to Biologically Inspired Robotics; Yunhui Liu and Dong Sun
CPG-Based Control of Serpentine Locomotion of a Snake-Like Robot; Xiaodong Wu and Shugen Ma
Analysis and Design of a Bionic Fitness Cycle; Jun Zhang, Ying Hu, Jianwei Zhang, Haiyang Jin, and Zhijian Long
Human-Inspired Hyperdynamic Manipulation; Aiguo Ming and Chunquan Xu
A School of Robotic Fish for Pollution Detection in Port; Huosheng Hu, John Oyekan, and Dongbing Gu
Development of a Low-Noise Bio-Inspired Humanoid Robot Neck; Bingtuan Gao, Ning Xi, Jianguo Zhao, and Jing Xu
Automatic Single-Cell Transfer Module; Huseyin Uvet, Akiyuki Hasegawa, Kenichi Ohara, Tomohito Takubo, Yasushi Mae, and Tatsuo Arai
Biomechanical Characterization of Human Red Blood Cells with Optical Tweezers; Youhua Tan, Dong Sun, and Wenhao Huang
Nanorobotic Manipulation for a Single Biological Cell; Toshio Fukuda, Masahiro Nakajima, and Mohd Ridzuan Ahmad
Measurement of Brain Activity Using Optical and Electrical Methods; Atsushi Saito, Alexsandr Ianov, and Yoshiyuki Sankai
Bowel Polyp Detection in Capsule Endoscopy Images with Color and Shape Features; Baopu Li and Max Q.-H. Meng
Classification of Hand Motion Using Surface EMG Signals; Xueyan Tang, Yunhui Liu, Congyi Lu, and Weilun Poon
Multifunctional Actuators Utilizing Magnetorheological Fluids for Assistive Knee Braces; H. T. Guo and W. H. Liao
Mathematical Modeling of Brain Circuitry during Cerebellar Movement Control; Henrik Jorntell, Per-Ola Forsberg, Fredrik Bengtsson, and Rolf Johansson
Development of Hand Rehabilitation System Using Wire-Driven Link Mechanism for Paralysis Patients; Hiroshi Yamaura1, Kojiro Matsushita, Ryu Kato, and Hiroshi Yokoi
A Test Environment for Studying the Human-Likeness of Robotic Eye Movements
Index
