A new method for face detection in colour images for emotional bio-robots

Emotional bio-robots have become a hot research topic in last two decades. Though there have been some progress in research, design and development of various emotional bio-robots, few of them can be used in practical applications. The study of emotional bio-robots demands multi-disciplinary co-operation. It involves computer science, artificial intelligence, 3D computation, engineering system modelling, analysis and simulation, bionics engineering, automatic control, image processing and pattern recognition etc. Among them, face detection belongs to image processing and pattern recognition. An emotional robot must have the ability to recognize various objects, particularly, it is very important for a bio-robot to be able to recognize human faces from an image. In this paper, a face detection method is proposed for identifying any human faces in colour images using human skin model and eye detection method. Firstly, this method can be used to detect skin regions from the input colour image after normalizing its luminance. Then, all face candidates are identified using an eye detection method. Comparing with existing algorithms, this method only relies on the colour and geometrical data of human face rather than using training datasets. From experimental results, it is shown that this method is effective and fast and it can be applied to the development of an emotional bio-robot with further improvements of its speed and accuracy.

A Preliminary Study of the Noninvasive Remote Control System for Rat Bio-Robot

A system is described here that can noninvasively control the navigation of freely behaving rat via ultrasonic,epidermaland LED photic stimulators on the back.The system receives commands from a remote host computer to deliver specifiedelectrical stimulations to the hearing,pain and visual senses of the rat respectively.The results demonstrate that the three stimuliwork in groups for the rat navigation.We can control the rat to proceed and make right and left turns with great efficiency.Thisexperiment verified that the rat was able to reach a setting destination in the way of cable with the help of a person through theappropriate coordination of the three stimulators.The telemetry video camera mounted on the head of the rat also achieveddistant image acquisition and helped to adjust its navigation path over a distance of 300 m.In a word,the non-invasive motioncontrol navigation system is a good,stable and reliable bio-robot.

A Biomimetic Approach to Robot Locomotion in Unstructured and Slippery Environments

While much attention has been given to bio-robotics in recent years, not much of this has been given to the challenging subject of locomotion in slippery conditions. This study begins to rectify this by proposing a biomimetic approach to generating the friction required to give sufficient propulsive force on a slippery substrate. We took inspiration from a successful biological solution-that of applying hair-like structures to the propulsive appendages, similar to the setae found in nereid polychaetes living in muddy habitats. We began by examining the morphology and the mean locomotion parameters of one of the most common nereids.. Nereis diversicolor. Following this study, we designed and fabricated a robotic system with appendages imitating the biological shape found in the worm. A flexible control system was developed to allow most of the locomotion parameters observed in the real worm to be applied to the robot. Experiments on three different natural substrates ranging from fine sand to gravel showed that, whereas a plate attached to the appendage generated most thrust on a small particle substrate, a bundle of artificial setae attached to the appendage generated most thrust on a large particle substrate. On all types of substrate tested, an appendage without any attachment did significantly worse than one with. This suggests that hair-like structures can be advantageous.

A Miniature Telemetric System for Freely Roaming Animals

Telemetric monitoring and control are the two critical aspects for a robot-rat. Development in this work is a telemetric system to record the electroencephalogram （EEG） from adult freely roaming animals. The system consists of two separated components： the transmit-end system, which consists of the preamplifier, the LPF （low-pass filter） and the transmitter, and the receive-end system, which consists of the receiver, the interface of receive-end and PC. The transmit-end system with light weight （10 g including battery） and small size （20 mm×50 mm） is fettered on the back of the rat. The EEG signal is modulated at the RF frequency of 2.4 GHz by nRF24E1 and transmitted by the antenna. The system can measure the EEG signal of the rat in freely roaming over a wireless transmission distance up to 8 m, and provide a new platform for behavioral and neurophysiological experiments.

Automatic Navigation for Rat-Robots with Modeling of the Human Guidance

A bio-robot system refers to an animal equipped with Brain-Computer Interface （BCI）, through which the outer stimulation is delivered directly into the animal＇s brain to control its behaviors. The development ofbio-robots suffers from the dependency on real-time guidance by human operators. Because of its inherent difficulties, there is no feasible method for automatic con- trolling of bio-robots yet. In this paper, we propose a new method to realize the automatic navigation for bio-robots. A General Regression Neural Network （GRNN） is adopted to analyze and model the controlling procedure of human operations. Com- paring to the traditional approaches with explicit controlling rules, our algorithm learns the controlling process and imitates the decision-making of human-beings to steer the rat-robot automatically. In real-time navigation experiments, our method suc- cessfully controls bio-robots to follow given paths automatically and precisely. This work would be significant for future ap- plications of bio-robots and provide a new way to realize hybrid intelligent systems with artificial intelligence and natural biological intelligence combined together.

A Radio-Telemetry System for Navigation and Recording Neuronal Activity in Free-Roaming Rats

A radio-telemetry recording system is presented which is applied to stimulate specific brain areas and record neuronal ac- tivity in a free-roaming rat. The system consists of two major parts： stationary section and mobile section. The stationary section contains a laptop, a Micro Control Unit （MCU）, an FM transmitter and a receiver. The mobile section is composed of the headstage and the backpack （which includes the mainboard, FM transmitter, and receiver）, which can generate biphasic mi- crocurrent pulses and simultaneously acquire neuronal activity. Prior to performing experiments, electrodes are implanted in the Ventral Posterolateral （VPL） thalamic nucleus, primary motor area （M1） and Medial Forebrain Bundle （MFB） of the rat. The stationary section modulates commands from the laptop for stimulation and demodulates signals for neuronal activity recording. The backpack is strapped on the back of the rat and executes commands from the stationary section, acquires neuronal activity, and transmits the neuronal activity singles of the waking rat to the stationary section. All components in the proposed system are commercially available and are fabricated from Surface Mount Devices （SMD） in order to reduce the size （25 mm×15 mm ×2 mm） and weight （10 g with battery）. During actual experiments, the backpack, which is powered by a rechargeable Lithium battery （4 g）, can generate biphasic microcurrent pulse stimuli and can also record neuronal activity via the FM link with a maximum transmission rate of 1 kbps for more than one hour within a 200 m range in an open field or in a neighboring chamber. The test results show that the system is able to remotely navigate and control the rat without any prior training, and acquire neuronal activity with desirable features such as small size, low power consumption and high precision when compared with a commercial 4-channel bio-signal acquisition and processing system.