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1. INTRODUCTION
1.1 Robots
A robot is a mechanical or virtual, artificial agent. It is usually an electromechanical system, which, by its appearance or movements, conveys a sense that it has intent or agency of its own.
A typical robot will have several, though not necessarily all of the following properties:
Is not 'natural' i.e. has been artificially created.
Can sense its environment.
Can manipulate things in its environment.
Has some degree of intelligence or ability to make choices based on the environment or automatic control / pre-programmed sequence.
Is programmable.
Can move with one or more axes of rotation or translation.
Can make dexterous coordinated movements.
Appears to have intent or agency (reification, anthropomorphisation or Pathetic fallacy).
Robotic systems are of growing interest because of their many practical applications as well as their ability to help understand human and animal behavior, cognition, and physical performance. Although industrial robots have long been used for repetitive tasks in structured environments, one of the long-standing challenges is achieving robust performance under uncertainty. Most robotic systems use a manually constructed mathematical model that captures the robot s dynamics and is then used to plan actions. Although some parametric identification methods exist for automatically improving these models, making accurate models is difficult for complex machines, especially when trying to account for possible topological changes to the body, such as changes resulting from damage.
1.2. Error Recovery
Recovery from error, failure or damage is a major concern in robotics. A majority of effort in programming automated systems is dedicated to error recovery. The need for automated error recovery is even more acute in the field of remote robotics, where human operators cannot manually repair or provide compensation for damage or failure.
Here, its explained how the four legged robot automatically synthesizes a predictive model of its own topology (where and how its body parts are connected) through limited yet self-directed interaction with its environment, and then uses this model to synthesize successful new locomotive behaviour before and after damage. These findings may help develop more robust robotics, as well as shed light on the relation between curiosity and cognition in animals and humans.
Fig 1.1 Robot
2. SELF HEALING OR SELF MODELLING ROBOTS
When people or animal get injured, they compensate for minor injuries and keep limping along. But in the case of robots, even a slight injury can make them stumble and fall .Self healing robots have an ability to adapt to minor injuries and continue its job . A robot is able to indirectly infer its own morphology through self-directed exploration and then use the resulting self-models to synthesize new behaviors. If the robot s topology unexpectedly changes, the same process restructures it s internal self-models, leading to the generation of qualitatively different, compensatory behavior. In essence, the process enables the robot to continuously diagnose and recover from damage. Unlike other approaches to damage recovery, the concept introduced here does not presuppose built-in redundancy, dedicated sensor arrays, or contingency plans designed for anticipated failures. Instead, our approach is based on the concept of multiple competing internal models and generation of actions to maximize disagreement between predictions of these models.
2.1 Researchers
This research was done at the Computational Synthesis Lab at Cornell University. Team members are Josh Bongard, Viktor Zykov, and Hod Lipson. Josh Bongard was a postdoctoral researcher at Cornell while performing this research and since then moved to the University of Vermont where he is now an Assistant Professor. Victor Zykov is a Ph.D. student at CCSL, and Hod Lipson is an Assistant Professor at Cornell, and directs the Computational Synthesis Lab. This project was funded by the NASA Program on Intelligent Systems and by the National Science Foundation program in Engineering Design.
2.2 The Starfish Robot
2.2.1 Characterizing the Target System
The target system in this study is a quadrupedal, articulated robot with eight actuated degrees of freedom. The robot consists of a rectangular body and four legs attached to it with hinge joints on each of the four sides of the robot s body. Each leg in turn is composed of an upper and lower leg, attached together with a hinge joint. All eight hinge joints of the robot are actuated with Airtronics 94359 high torque servomotors. However, in the current study, the robot was simplified by assuming that the knee joints are frozen: all four legs are held straight when the robot is commanded to perform some action. The following table gives the overall dimensions of the robot s parts.
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Submitted by AKHIL
ABSTRACT
When people or animals get hurt, they can usually compensate for minor injuries and keep limping along, but for robots, even slight damage can make them stumble and fall. Now a robot scarcely larger than a human hand has demonstrated a novel ability: It can recover from damage -- an innovation that could make robots more independent.
The new robot, which looks like a splay-legged, four-footed starfish, deduces the shape of its own body by performing a series of playful movements, swiveling its four limbs. By using sensors to record resulting changes in the angle of its body, it gradually generates a computerized image of itself. The robot then uses this to plan out how to walk forward.
The researchers hope similar robots will someday respond not only to damage to their own bodies but also to changes in the surrounding environment. Such responsiveness could lend autonomy to robotic explorers on other planets like Mars -- a helpful feature, since such robots can't always be in contact with human controllers on earth. Aside from practical value, the robot's abilities suggest a similarity to human
thinking as the robot tries out various actions to figure out the shape of its world.
INTRODUCTION
ROBOTS
A robot is a mechanical or virtual, artificial agent. It is usually an electromechanical system, which, by its appearance or movements, conveys a sense that it has intent or agency of its own.
A typical robot will have several, though not necessarily all of the following properties:
Is not 'natural' i.e. has been artificially created.
Can sense its environment.
Can manipulate things in its environment.
Has some degree of intelligence or ability to make choices based on the environment or automatic control / pre-programmed sequence.
Is programmable.
Can move with one or more axes of rotation or translation.
Can make dexterous coordinated movements.
Appears to have intent or agency (reification, anthropomorphisation or
Pathetic fallacy).
Robotic systems are of growing interest because of their many practical applications as well as their ability to help understand human and animal behavior, cognition, and physical performance. Although industrial robots have long been used for repetitive tasks in structured environments, one of the long-standing challenges is achieving robust performance under uncertainty. Most robotic systems use a manually constructed mathematical model that captures the robot s dynamics and is then used to plan actions. Although some parametric identification methods exist for automatically improving these models, making accurate models is difficult for complex machines, especially when trying to account for possible topological changes
to the body, such as changes resulting from damage.
ERROR RECOVERY
Recovery from error, failure or damage is a major concern in robotics. A majority of effort in programming automated systems is dedicated to error recovery. The need for automated error recovery is even more acute in the field of remote robotics, where human operators cannot manually repair or provide compensation for damage or failure.
Here, its explained how the four legged robot automatically synthesizes a predictive model of its own topology (where and how its body parts are connected) through limited yet self-directed interaction with its environment, and then uses this model to synthesize successful new locomotive behaviour before and after damage. These findings may help develop more robust robotics, as well as shed light on the relation between curiosity and cognition in animals and humans.
SELF HEALING OR SELF MODELLING ROBOTS
When people or animal get injured ,they compensate for minor injuries and keep limping along. But in the case of robots, even a slight injury can make them stumble and fall .Self healing robots have an ability to adapt to minor injuries and continue its job . A robot is able to indirectly infer its own morphology through self- directed exploration and then use the resulting self-models to synthesize new behaviors.If the robot s topology unexpectedly changes, the same process restructures it s internal self-models, leading to the generation of qualitatively different, compensatory behavior. In essence, the process enables the robot to continuously diagnose and recover from damage. Unlike other approaches to damage recovery, the concept introduced here does not presuppose built-in redundancy, dedicated sensor arrays, or contingency plans designed for anticipated failures. Instead, our approach is based on the concept of multiple competing internal models and generation of actions to maximize disagreement between predictions of these models.
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This article is presented by:
A SEMINAR REPORT
Submitted by
AKHIL
ABSTRACT
When people or animals get hurt, they can usually compensate for minor injuries and keep limping along, but for robots, even slight damage can make them stumble and fall. Now a robot scarcely larger than a human hand has demonstrated a novel ability: It can recover from damage -- an innovation that could make robots more independent. The new robot, which looks like a splay-legged, four-footed starfish, deduces the shape of its own body by performing a series of playful movements, swiveling its four limbs. By using sensors to record resulting changes in the angle of its body, it gradually generates a computerized image of itself. The robot then uses this to plan out how to walk forward. The researchers hope similar robots will someday respond not only to damage to their own bodies but also to changes in the surrounding environment. Such responsiveness could lend autonomy to robotic explorers on other planets like Mars -- a helpful feature, since such robots can't always be in contact with human controllers on earth. Aside from practical value, the robot's abilities suggest a similarity to human thinking as the robot tries out various actions to figure out the shape of its world.
INTRODUCTION
1.1 ROBOTS
A robot is a mechanical or virtual, artificial agent. It is usually an electromechanical system, which, by its appearance or movements, conveys a sense that it has intent or agency of its own. A typical robot will have several, though not necessarily all of the following
properties:
Is not 'natural' i.e. has been artificially created.
Can sense its environment.
Can manipulate things in its environment.
Has some degree of intelligence or ability to make choices based on the
environment or automatic control / pre-programmed sequence.
Is programmable.
Can move with one or more axes of rotation or translation.
Can make dexterous coordinated movements.
Appears to have intent or agency (reification, anthropomorphisation or
Pathetic fallacy).
Robotic systems are of growing interest because of their many practical applications as well as their ability to help understand human and animal behavior, cognition, and physical performance. Although industrial robots have long been used for repetitive tasks in structured environments, one of the long-standing challenges is achieving robust performance under uncertainty. Most robotic systems use a manually constructed mathematical model that captures the robot s dynamics and is then used to plan actions. Although some parametric identification methods exist for automatically improving these models, making accurate models is difficult for complex machines, especially when trying to account for possible topological changes to the body, such as changes resulting from damage.
Self Healing Robots
Division of Computer Science and Engineering
2
1.2. ERROR RECOVERY
Recovery from error, failure or damage is a major concern in robotics. A majority of effort in programming automated systems is dedicated to error recovery. The need for automated error recovery is even more acute in the field of remote robotics, where human operators cannot manually repair or provide compensation for damage or failure. Here, its explained how the four legged robot automatically synthesizes a predictive model of its own topology (where and how its body parts are connected) through limited yet self-directed interaction with its environment, and then uses this model to synthesize successful new locomotive behaviour before and after damage. These findings may help develop more robust robotics, as well as shed light on the relation between curiosity and cognition in animals and humans.
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ANJALI.N.V
MEASUREMENT OF OPTICAL PROPERTIES OF HUMAN SKIN
In this, a very convenient approach has been made to determine the skin optical properties in-vivo using a simple optical fiber spectrophoto-meter. This method realises the determination of the optical properties of living tissue with the help of diffuse reflectance emitted from the skin when a mutiple wavelength light is incident on it. Oblique Incidence Diffuse Reflectance Spectrometry (OIDRS) is an optical method capable of quantifying both absorption coefficient and scattering coefficient of heterogenous media like skin with the help of the diffuse reflectance of the media. This will greatly assist in the diagnosis and even treatment of its pathologies. The dermatologist is able to identify the affected skin , by colour and other visual textural characteristics of the spectral images obtained fron the spectrophotometer.
INTRODUCTION
Skin cancers and tumors are an increasing problem around the world. Skin cancers account for about 40% of all the diagnosed cancers. Almost all skin cancers are curable, if detected early. Some cause morbidity if untreated. Currently, clinical dermatologists rely on visual inspection and experience to make an initial assessment of the skin lesion state. If further visual analysis does not provide a conclusive decision on the lesion state, such suspicious lesions are sent for biopsy analysis. Biopsy is unpleasant for the patient,slow in diagnostic results, and costly for the hospital on account of the wait time. Dermatologists would greatly benefit from a fast and noninvasive technique that could assist them in their clinical diagnostic decisions. Recent studies have suggested the close relationship between the various stages of skin diseases and the optical properties of the affected area. Finding the optical properties help a lot in the diagnosis. All the photo biological effects which are responsible for the variations in the optical properties of skin like the UV irradiation [which causes erythema (skin reddening), stimulates melanin synthesis, and even induce edema and tissue proliferation if the radiation dose is sufficiently large] need to be taken into consideration when prescribing phototherapy. So we need to find the optical properties of human skin.
OPTICAL PROPERTIES OF HUMAN SKIN
In terms of optical properties, biotissues (including blood, lymph, and other biological fluids) can be categorized into two large classes
strongly scattering (opaque) tissues such
as skin, brain, vascular walls, blood, and
weakly scattering (transparent) tissues such as the cornea and lens in the anterior eye chamber
Optical properties of human skin vary according to age and race. Biological tissues are optically inhomogeneous absorption media whose average refractive index is higher than that of air. This account for the partial reflection of radiation at the tissue/air interface (Fresnel reflection) while the remaining part penetrates the bio object. Multiple scattering and absorption are responsible for laser beam broadening and eventual decay as it travels through a biotissue whereas volume scattering is a major cause of the dispersion of a large fractionof radiation in the backward direction (backscattering).
Cellular organelles such as mitochondria are the main scatterers in various biotissues. Absorbed light is converted to heat and reradiated in the form of fluorescence; it is also consumed in photo-biochemical reactions. The absorption spectrum depends on the type of predominant absorption centers and water content of biotissues.
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Aarathi Vikas
S7 CSE
INTRODUCTION
Self healing robots have ability to adapt to minor injuries
A robot is able to infer its own morphology through self directed exploration
The concept used is multiple competing internal models and generation of actions
THE STARFISH ROBOT-CHARACTERIZING THE TARGET SYSTEM
The target system is a quadrapedal, articulated robot
It consist of a rectangular body and four legs attached to it with a hinge joint
Each leg has a upper and lower leg attached together with a hinge joint
All eight hinge joints are actuated with high torque servomotors
Servo drives capable of producing max 200 ounceinches of torque and 60o per second speed
Robot can automatically synthesize predictive models of its own topology
Equipped with suite of different sensors
SELF MODELLING BRIEFLY
Robots depend on internal maps and sensory data to update their location
In a changing environment the robot has to navigate with uncertainity
Situation becomes even worse if the robot s own shape and configuration can change
PHASES IN SELF HEALING
Self Model synthesis
Exploratory Action synthesis
Target Behaviour synthesis
ALGORITHM
Estimation-exploration algorithm is used
It has 2 functions: damage hypothesis evolution and controller evolution
It maintains a database which stores pairs of data
STEPS INVOLVED .
Exploration phase: Controller evolution
Physical robot failure
Estimation Phase: Damage hypothesis evolution
EXPERIMENTAL SETUP
The quadrapedal robot has eight degrees of freedom
Two one degree-of-freedom rotational joints per leg:one at the shoulder and one at knee
It has 4 binary touch sensors and also 4 angle sensors
All joints are actuated by a torsional motor
THE CONTROLLERS
Robots are controlled by a neural network
There are 3 layers in the neural network-input layer,hidden layer,output layer
SELF HEALING ROBOTS
When people or animals get hurt, they can usually compensate for minor
injuries and keep limping along, but for robots, even slight damage can make them
stumble and fall. recovering from damage is an innovation that could make robots
more independent.
It basically looks like a a splay-legged, four-footed starfish and knows the the shape of its own body by performing a series of playful movements. changes in the angle of its body are sensed by sensors and a computerized image of the robot is generated. Ie it uses self- directed exploration to respond and readjust If the robot s topology unexpectedly changes.
THE STARFISH ROBOT
CHARACTERIZING THE TARGET SYSTEM:
A quadrupedal, articulated robot with eight
actuated degrees of freedom is the target system described here. The rectangular body has four legs attached to it with hinge joints. a 16-bit 32-
channel PC-104 Diamond MM-32XAT data acquisition board polls the sensors of the robot.
SELF MODELLING BRIEFLY:
The following are the steps taken by the robot for remodelling itself:
Fitst, the robot performs an arbitrary motor action and
records the resulting sensory data. 15 candidate self-models is created by model synthesis component . these models are used to to find a new action most likely to elicit the most information from the robot by a action synthesis
component . most accurate model is created after 16 iterations. Then a compensating behavior is done to recover functionality.
For full report, visit the link:
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