The utilization of autonomous intelligent robots in search and rescue (SAR) is a new and challenging field of robotics, dealing with tasks in extremely hazardous and complex disaster environments. Autonomy, high mobility, robustness, and modularity are critical design issues of rescue robotics, requiring dexterous devices equipped with the ability to learn from prior rescue experience, adaptable to variable types of usage with a wide enough functionality under different sensing modules, and compliant to environmental and victim conditions. Intelligent, biologically inspired mobile robots and, in particular, serpentine mechanisms have turned out to be widely used robot effective, immediate, and reliable responses to many SAR operations. This article puts a special emphasis on the challenges of serpentine search robot hardware, sensor-based path planning, and control design.
In the past two decades it is estimated that disasters are responsible for about 3 million deaths worldwide, 800million people adversely affected, and property damage exceeding US$50 billion. The recent earthquake in Turkey in November of 1999 left 700 dead and 5000 injured. Many of these deaths were from structural collapse as buildings fell down onto people. Urban Search and Rescue involves the location, rescue (extrication), and initial medical stabilization of victims trapped in confined spaces. Voids formed when a buildings collapse is one instance of a confined space. Urban Search and Rescue may be needed for a variety of situations, including earthquakes, hurricanes, tornadoes floods, fires, terrorist activities, and hazardous materials (hazmat) accidents. Currently, a typical search and rescue team is composed of about ten people, including canine handlers and dogs, a paramedic, a structural engineer, and various specialists in handling special equipment to find and extract a victim. Current state of the art search equipment includes search cameras and listening devices. Search cameras are usually video cameras mounted on some device like a pole that can be inserted into gaps and holes to look for signs of people. Often a hole is bored into the obstructing walls if a void is suspected to exist on the other side. Thermal imaging is also used. This is especially useful in finding warm bodies that have been coated with dust and debris effectively camouflaging the victim. The listening devices are highly sensitive microphones that can listen for a person who may be moving or attempting to respond to rescuers calls. This hole process can take many hours to search one building. If a person is found extrication can take even longer. This paper presents the developments of a modular robot system towards USAR applications as well as the issues that would need to be addressed in order to make such a system practical.
Recent natural disasters and man-made catastrophes have focused attention on the area of emergency management arid rescue.These experiences have shown that most governmentâ„¢s preparedness and emergency responses are generally inadequate in dealing with disasters. Considering the large number of people who have died due to reactive, spontaneous, and unprofessional rescue efforts resulting from a lack of adequate equipment or lack of immediate response, researchers have naturally been developing mechatronic rescue tools and strategic planning techniques for planned rescue operations. Research and development activities have resulted in the emergence of the field of rescue robotics, which can be defined as the utilization of robotics technology for human assistance in any phase of rescue operations, which are multifacetted and vary from country to country due to regional policies, the types of disasters, and the different compositions of rubble in the disaster areas. Other aspects of rescue robotics include:
Â¢ Detection and identification of living bodies
Â¢ Routing and/or clearing of debris in accessing the victim
Â¢ Physical, emotional, or medical stabilization of the survivor by bringing to him/her automatically administered and telemetered first aid
Â¢ Fortification of the living body for secure retrieval against any falling debris and possible injuries
Â¢ Transportation of the victim.
These operations also vary in character for different kinds of disaster environments, such as urban areas, underground, or underwater, which are unstructured and technologically difficult for humans to access. The critical issues in rescue are the expediency and compliance of rescue tools. The other major rescue problems encountered are:
Â¢ Nondexterous tools are generally cumbersome, destructive, and usually directly adapted from construction devices.
Â¢ Debris-clearing machines are heavy construction devices that, when functioning on top of rubble, trigger the rubble to cave in.
Â¢ Tool operation is generally very slow and tedious and does not take into consideration prior attempts on the same spot (they do not learn from the on-the-spot trials), yielding many unsuccessful repetitions.
Â¢ Although a few detectors are available, the search for survivors is mainly based on sniffing dogs and human voices, where calling and listening requires silence and focused attention that is very difficult due to over- worked, exhausted, and depressed rescue workers.
Â¢ The supply of first-aid can only be done when at close proximity to the survivor, a distance frequently reached when the critical timing for survival is exceeded.
Â¢ The retrieval of bodies generates extra injuries since professional stabilization of the victim is seldom obtained and is not continuously monitored.
Aiming at enhancing the quality of rescue and life after rescue, the field of rescue robotics is seeking dexterous devices that are equipped with learning ability, adaptable to various types of usage with a wide enough functionality under multiple sensors, and compliant to the conditions of the environment and that of the person being rescued.
Constraints on Robotic Rescue Devices
The field of rescue robotics is seeking to develop the closest possible relationship between humans and machines in emergency situations, leading the way to the possible substitution of men by machines, based on their autonomy. Adjustable autonomy, shape-shifting robots (holonic robots equipped with multiple sensing modules) provide the necessary flexibility and adaptability needed in the difficult workspaces of rescue missions. Robotic rescue devices have to work in extremely unstructured and technically challenging areas shaped by natural forces. One of the major requirements of rescue robot design is the flexibility of the design for different rescue usage in disaster areas of varying properties. Any two disasters of tie same type do not have damages that are alike and, in the same disaster, no two regions are likely to exhibit similar damage characteristics. Thus, rescue robotic devices should be adaptable, robust, and predictive in control when facing different and changing needs. They should be compliant to the environment, to changing tasks, and be intelligent in order to handle all disturbances generated from different sources of parametric and nonparametric uncertainty.
Rescue robots should be equipped with a multitude of sensors of different types and resolution since detection, identification, and tracking of survivors should continuously be performed. As mentioned in sensors are the weakest components in the rescue system. They need to be robust in data acquisition, with enough intelligence to minimize errors and orient themselves towards maximum signal intensity. Sensors can assume a distributed role in control when embedded in sensing modules, generally called logical sensors. Robotic devices should be cheap enough so that they can be manufactured and used in rescue operations en masse. This redundancy in number is critical in order to compensate for failures in rescue mission performance. The loss of these devices should not be highly expensive. Thus, multiple inexpensive and less accurate sensors should be onboard devices rather than expensive specialized detectors. This leads to the need for sensor and decision fusion in rescue robots to increase the robustness in sensing and control, putting a computational burden on data processing.
SERPENTINE RESCUE ROBOTS: LEADING APPROACHES
Sensor-Based Online Path Planning
This section presents multisensor-based online path planning of a serpentine robot in the unstructured, changing environment of earthquake rubble during the search of living bodies. The robot presented in this section is composed of six identical segments joined together through a two-way, two degrees-of- freedom (DOF) joint enabling yaw and pitch rotation (Fig.), while our prototype mechanism (to be discussed later in this article) is made of ten joints with 1 DOF each.
Configuration of each segment
The robot configuration of this section results in 12 controllable DOF. An ultrasound sensor, used for detecting the obstacles, and a thermal camera are located in the first segment (head). The camera is in a dust free, anti shock casting and operates intermittently when needed. Twelve infrared (IR) sensors (Six pairs) are located on the left and right of the joints of the robot along its body (Fig.)
Mechanical layout of the Front section of the snakelike robot
Local map building
Modified distance transform
The modified distance transform (MDT) is the original distance transform method modified for snake robot such that the goal cell is turned in to a valley of zero values within which the serpentine robot can nest. Other modifications are also made to render the method on line
Â¢ Distance transform is first computed for the line of sight directed towards the intermediate goal, without taking into account sensorial data about obstacles and free space. This is the goal-oriented planning.
Â¢ The obstacle cells are superimposed on the cellular workspace. This modification to the original distance transform integrates IR data that represent the obstacles are assigned high values.
This modification of partitioning the distance transform (DT) application into goal oriented and range-data oriented speeds up the planning considerably, rendering it online. It is also observed that DT performed for an intermediate goal at an angular displacement from the line of sight different than zero angle displacement first. Then, the resultant workspace matrix is rotated by the required goal angle. Since the matrix resolution is finite (in our case 100*100), some cells remain unassigned. Therefore, we pass the matrix through a median filter that removes glitches in local map caused by un assigned cells.
MDT- Based exploratory path planning methodology
The major aim of the serpentine search robot is to find and identify living beings under rubble and lock onto their signals until they are reached. Therefore, local map building is an essential component of our path planning approach. Since the objects in the rubble environment are expected to change position and orientation, the local map is used to find the next desired position of the robot on its way to a goal, the living being, placed in an initially unknown but detected location.
The ultrasound sensor scans to determine obstacles and free space and develops a local map. Thus, sensory data constructs a local map within this sensor range. After the local map is obtained, the next possible intermediate goals are found by considering points that are at the middle of the arcs representing free space. The intermediate goal is selected from the candidate next states by considering the directions of the candidate states relative to the robotâ„¢s head. In real applications, the direction that gives the highest signal energy (thermal, sound) received from the goal (living being) is selected as an intermediate goal. The intermittent function of the camera is also used for choosing the most appropriate intermediate goal. However, in the simulation here, we represent, for illustrative purposes, the magnitude of the signals coming from the main goal as inversely proportional to the distance between sensor and goal. Thus, this distance becomes minimum when the robot sensor faces the goal that is an emulation of the maximum signal energy coming from the goal. After the intermediate goal is found, the MDT method is applied, and the robot moves to this intermediate goal by using the serpentine gaits that are selected from those with minimum cost in the output of MDT. The cost function F(s) of the possible next gait state s is formulated as
Where wi is the weight of the ith control point, and C(xi ,yi) is the cost value obtained from the MDT for the ith control point located at xi and yi. Six discrete control points are taken into consideration and are used for calculating a cost function for a gait. These control points are used to find the candidate cells where each of the robot segments could possibly move after deciding upon a gait. So, each of these cell values are multiplied with a weight value representing the possibility in candidacy of each cell and added to the cost function. Weights of control points i depend on the ranking of the importance of contribution of each segment i to the snake displacement. This importance is a degree of constraint put on that segment during serpentine locomotion. A gait is selected such that it has minimum cost, which is a way of demonstrating that this gait is the one that requires the least body energy in its realization in the corresponding local map. Thus, we assign weights for each control point such that the front section has the maximum value and the end section has the minimum value. When the snake has to backtrack on its path, the weights are reversed: the tail portion having maximum value and the front a minimum value. After reaching the intermediate goal, the robot makes a new scan and determines a next intermediate goal in this new local map. This process is repeated until the robot reaches the closest neighborhood of the main goal. Fig represents a sample of (snake + environment) interactions tracked by a simulation program, while Fig.4 shows the local map built by sensory data obtained for this (snake + closest-environment) interaction. In Fig, the fishbone structure on the robot shows the line of sight of the IR sensor pairs located on each side of the snake robot, while the front radial line is the line of sight of the ultrasound sensor. The small squares in the middle of the arc are the candidates for the intermediate goal. The suitable goal is selected according to its direction relative to the main goal. As stated previously, the one that is closer to the main goal is selected as the next intermediate goal.
A sample environment of the simulation
The cubic obstacle head-front from the snake robot in Fig. is clearly seen in the local map of Fig. In this figure, the different gray levels represent the cost values obtained from MDT, where darker regions represent minimum values and brighter regions represent the higher cost values. Since the dimension of a local map is much smaller than that of a global map, the errors related to location and orientation of the robot are minimized when compared to finding the location with a global map. When the intermediate goal is reached, the current local map is not needed anymore, a new local map is constructed, and a new intermediate goal is selected.
Local map obtained from the sensors
Serpentine gaits of the search robot
The locomotion of the snake-like robot is achieved by adapting the natural snake motions to the multisegment robot configuration. For the current implementation, the robot has four possible gaits that result in four possible next states.
Â¢ Move forward with rectilinear motion or lateral undulation (two separate gaits): In rectilinear motion, the segments displace themselves as waves on the vertical axis. In lateral undulation, the snake segments follow lines of propagating waves in the horizontal 2-D plane.
Â¢ Move right/left with flapping motion (flap right/left): In flapping, two body parts of the robot undergo a rowing motion in the horizontal plane with respect to its center joint and then pull that center. This results in parallel offset displacement.
Â¢ Change of direction right/left with respect to the pivot located near the middle of the robot: The robot undergoes a rotation in the horizontal plane to the right or left with respect to the joint at or nearest to the middle of the snake.
A sample locomotion sequence is shown in Fig. Since the robot starts its next gait with initial line up (reset) and ends the gait with a final line up, the robot is shown as a line in these local maps. In the last version of our method, this resetting is optional and can be omitted, allowing the snake-like robot to proceed into a new gait from the body shape acquired from the last accomplished gait. After the local map is built, the robot decides the next gait using MDT, then lines up if resetting is possible, simplifying computational load. If this is not possible, the snake robot directly implements the selected gait from its previously acquired body shape. Intermediate goals are used to proceed towards the main goal. Sample simulation results are shown in Fig.5, which shows the displacement of the snake-robot among obstacles. This sample shows the path followed by the robot as composed of lines and arcs that are the result of the serpentine gaits used by the snake like robot. Straight lines in the direction of the robot are formed by rectilinear motion. Short lines deviating from the main path are formed by flapping motions. The arcs on the path are formed by rotational motion.
Robot movements in local map
DEVELOPMENT OF THE PROTOTYPE MECHANISM
As stated earlier, rescue applications in disaster scenarios require robotic mechanisms to be hyper- redundant mechanisms that allows the mechanisms to effectively adapt to uncertain circumstances and carry out required activates with necessary flexibility. The basic units are concatenate in series to create a simple yet flexible hyper-redundant robotic prototype- some of which are shared in this article.
The specifications of the basic components of the units are made of super-duralumin alloy get a lightweight structure. The nominal size of the fabrication units is 82 X 82 X 67 mm with a weight of 300gms. The units have a single joint of 1DOF.This units are equipped with stepper motor to drive the joints, making it possible to have position as well as velocity control of the joint movements. The torque generated by about 34times through a series of gear mechanisms. This results in a maximum available torque of 20 kgf/cm and the maximum angular speed of 500 /s. when the units are connected in series, this nominal specification allows each joint a capability to lift five similar units, connected in series, from a horizontally extended configuration. Potentiometers are installed in the units to measure the angular position of the joints axis. The present design allows a maximum +/- 600 range of angular movement. To limit switches are used to sense the extremities of the moving components that are used by the logic circuit to override the motor controller and activate or deactivate the actuation.
One of the special features of the present design of the basic unit is that the unit can be concatenated with the optional 900 shift between the adjacent unit (Fig). This option makes it possible to assemble a hyper-redundant mobile robot with movements in 3-D space. The unit also allows the option of attaching passive wheels to enable serpentine movement on relatively flat surface. A brief description of some possible modes (serpentine gaits) is mentioned below.
Â¢ Twisting mode: In this mode, the robot mechanism folds certain joints to generate a twisting motion within its body, resulting in a side-wise movement.
Â¢ Wheeled-locomotion mode: This is one of the common wheeled-locomotion modes where passive wheels (without direct drive) are attached on the units, resulting in low friction along the tangential direction of the robot body line and increasing the friction in the direction perpendicular to that .
Â¢ Bridge mode: In this mode the robot configures itself to stand on its two end units in a bridge-like shape. This mode has the possibility of implementing two-legged walking-type locomotion. The basic movement consists of left-right swaying of the center of gravity in synchronism by lifting and forwarding one of the supports like, bipeclal locomotion. Motions such as somersaulting may be other possibilities.
Â¢ Ring mode: The two ends of the robot body are brought together by its own actuation to form a circular shape. The drive to make the uneven circular shape rotate is expected to be achieved by proper deformation and shifting of the center of gravity as necessary.
Â¢ Inching mode: This is one of the common undulatory movements of serpentine mechanisms. The robot generates a vertical wave shape using its units from the rear end and propagates the wave along its body, resulting in a net advancement in its position.
Specification of prototype unit
Actuator Stepping Motor
Material Aluminum alloy
Dimension 82 x 82 x 67 mm3
Weight 300 g
Max. Torque 20 Kgf/cm
Max. Angle Velocity 500 /s
Workspace +/- 600
The following sections will consider the twisting mode and the wheeled locomotion mode and will present some of the preliminary results.
Twisting Mode of Locomotion
In the twisting mode, two of the joints of the robot body are bent in a way that the rest of the body experiences a twisting force, resulting in a side-wise shift after each twist. Since, in this case, no other parts of the robots are moved, the robot can effectively be considered as a three link robot. Since, in this mode, the number of actuated joints is very small, this is a very fault-tolerant mode of movement. Even in the case of the failure of a number of joints, this mode may be applicable. In Fig., the method of generation of the twisting motion is shown.
In the present work, two joints are assembled with a 900 shift and actuated to realize the desired motion. As shown in Fig. the adjacent unit axles (with 90Ã‚Â° offset) are referred as j1 and j2. Let zi be the rotational axis of the ith joint ji. Let us refer the three effective links as L1, L2 and L3. Let the initial condition (state 1) be that L1 is displaced by a relative angle of , with respect to L2 (by the joint j1) and the relative angle between L1 and L3 is kept to 00 (by the joint j2) It is assumed that all other links are fixed in a straight-line alignment, i.e., the relative angular displacement between the adjacent links is 00.
From this initial state, the joint j1 is driven in the counter clockwise (positive) direction and joint j2 in clockwise (negative) direction at the same time (state 2). When the relative angle at j1 becomes 0Ã‚Â°, and the relative angle at j2 becomes d the robot body turns to one side by 90Ã‚Â° (state 3), as shown in Fig. .
An example of twisting locomotion using the developed prototype is shown in Fig. In that assemblage, each consecutive unit is offset by 90Ã‚Â°, and ten such units are connected together. The fifth and sixth units from one end are used for the actuation drive. If the active units are driven by two 90Ã‚Â° phase-shifted sine waves, the robot body will generate a smooth and continuous side-turning locomotion. In Fig., three consecutive 90Ã‚Â°, turning-action sequences are shown.
To realize smooth, undulatory serpentine movement, it has been shown that there must be a large difference between the friction along the tangential direction and the perpendicular direction at any point of the robot body. In the present work, as shown in Figs (schematic and prototype), drive-less, passive wheels are attached to the units. This makes it possible to achieve that necessary condition of undulatory motion.
Wheeled- locomotion mode
If a sinusoidal drive is applied to the joints with proper positional phase difference, the mechanism will move forward following a serpentine curve. In this mode, it is possible to get faster locomotion on a relatively flat surface. On the other hand, on uneven or irregular surfaces, this mode of locomotion is not likely to be an effective option. Also, in the case of surfaces with very low friction (e.g., over ice), efficiency is likely to be low. The top-view of the prototype motion in this mode is shown in Fig.
The frames in Fig.13 are taken at an interval of 4 s, and the distance scale is marked with 50-cm separation. In the prototype, ten units are connected with 90Ã‚Â° offset of the joint axis. Thus, five of the units are actually in contact with the floor. In the experiment shown, actuation was given to those five units only, and the other joints are kept fixed. Those fixed joints may also be driven if movement in the third dimension is desired. In the experiment, the actuations are designed to generate a sinusoidal angular displacement of joint axes with a frequency of0.12 Hz. The amplitude of angular oscillation of the active joints was selected to be 24Ã‚Â°. The sinusoidal drives between the consecutive active joints are time shifted by an amount of 1.75 s. The resulting net forward motion of the robot was 4.0 cm/s.
A GA-Based Planning of Shape Transition
To transform the shape of the hyper-redundant robotic mechanism from one shape to another without losing structural stability, proper planning methodology is essential. In this section, one of the possible methods of shape transformation planning, using a genetic algorithm (GA) is considered. In the example situation described below, transformation of the multi-unit serpentine robot structure from resting horizontal configuration to a bridge configuration is considered. The desired result is to make the mechanism stand on its two ends in a vertical position. In this case, a ten-unit-long assembly is considered, without relative angular shift between the joint axes.
The transformation from the initial to the final configuration is divided in k intermediate configurations. The genetic search algorithm is used to find the optimal (according to the desired fitness function) set of those k configuration sequences through which the robot shape is to be transformed. Each configuration in the genotype is described as the sequence of relative joint angles of the robot body. The whole chromosome structure is encoded as shown in the following expression.
Where represents the ith relative joint angle in the ith configuration sequence.
To find the optimal sequence of joint angles, several performance indices are considered, and a weighted combination of them is used as the overall fitness function for the genetic search. The performance indices, considered in the present example are stability margin of the structure, smoothness of angular transformations between successive shapes, and smoothness in positional change of the center of gravity from one shape to the next.
The detail definitions of the indices and other issues of GA search parameters are considered elsewhere. The result of the GA search is shown in Fig. In Fig. the dot (Â¢) marks represent the joint position and the cross (X) mark represents the center of gravity of the whole robot body. From Fig., the stable and smooth transformation from the initial through the final state can be observed. The actual implementation of the transformation sequence by the prototype mechanism is shown in Fig. The interval between the successive frames, shown in Fig. is 4s.
Â¢ Bridge inspection
The proposed research will develop and innovative technology which resolves these short comings. Instead, an inspector, sitting in a truck on the bridge roadbed, will control a robot which can "view" the entire bridge through a sensor suite deployed at the end of the robot. This system would reduce the cost of bridge inspection, increase the safety factor, provide better views of the bridge, improve the quality of information, and as an added benefit, decrease traffic delays that are a result of such an operation.
Â¢ Rescue operation under trench
Another SAR application that has received little attention is the rescue of victims in a trench collapse. This is not usually the result of a major disaster like an earthquake, rather these collapses occur while workmen are digging or fixing pipes or other underground equipment. Because this is more mundane, it receives less press, however the frequency of this accident is much higher. Small robots that can go through sewer pipes or other underground conduits may be able to find victims. Small robots that can dig may also be able to find victims more readily.
Â¢ Small in size and weight
Modular reconfigurable robots with many modules have the ability to form a large variety of shapes with large numbers of degrees of freedom (DOF). The robot may change its shape to suit different environments. In this fashion the robot is very versatile. For USAR, the same system could do a variety of tasks. A robot could start in the shape of a snake to slither through small cracks and holes and pipes to find a victim. In addition to being highly mobile, the versatility
of the system allows it to achieve other tasks in the highly constrained environment such as shoring the structure near a victim. An air hose may also be brought to the victim to provide ventilation in the confined area both to provide oxygen to breathe as well as removal of possible toxic or flammable gases.
In many extrications, shoring is an integral part. If the unstable material cannot be removed from above the victim (for example if a person is trapped on the lower floors of an unstable multi-story building,) the ceilings and walls need to be shored to prevent further collapse before rescuers can attempt to reach the victim. One measure of the versatility of a modular system may be the number of isomorphic configurations that are capable by a given system . For many systems, this number grows exponentially with the number of modules. Another measure may be the number of DOF in the system. This also grows with the number of modules though linearly in this case.
Another result of being modular and reconfigurable is the ability of the system to repair itself . When a system has many identical modules and one fails, any module can replace it. Another factor increasing the reliability is that a moduleâ„¢s area of influence is typically local. If one module is not working properly, since it can only affect things locally, the errors it introduces may be able to be compensated by the modules around it. Basically there are redundant modules that can either compensate or replace failing modules. As the number of modules increases, the redundancy also increases. This may be critical in unstable environments.
Â¢ Low expenses
As the numbers of repeated modules increases, the economies of scale come into play and the per-module cost goes down. Again, increasing the numbers of modules enhances this effect. On the other hand, the total number of modules still increases. The question of exactly which factor effects the total cost of the system the most is difficult to predict without implementing a full system to determine the components needed and their relative costs.
Â¢ Cannot optimize its own path
Â¢ Hard to control
Snake robots have many applications, but are hard to control. A person cannot simply operate each joint of a snake individually because there are too many. These robots require a motion planning algorithm. Motion planning for snake robots is difficult because the robots have many internal degrees of freedom that have to be coordinated to achieve purposeful motion. In motion planning jargon, this means the snake robots exist in large dimensional configuration spaces. Our work will make it possible for the robots to operate in several different modes from fully autonomous to human-guided
SAR robotics is aiming at developing dexterous device equipped with the ability to learn from prior rescue experience that are adaptable to variable types of usage with a wide enough gait functionality under different sensing modules an are compliant to the environmental and victimâ„¢s conditions Multiâ€agent systems are, likewise, focusing on adaptability multifunctionality through modularity, and dexterity, where intelligence is the basic property of the agents.
Biological1y inspired robots (specifically, snakeâ€ and worm-like robots with modularity and hyper-redundancy) generally perform detection and identification of victims an path planning in search of survivors to be rescued using decision and control methodologies from the aforementioned concepts without collision. Serpentine mechanisms, with their wide range of capabilities, face major design challenge mechanism design, path planning, control, and sensor integration. This research addresses control and sensor integration path planning and an actuated joint module that is design and implemented as the basic component of a serpentine rob platform. A number of such modules can be connected in desired way to create a simple yet flexible hyper-redundant serpentine structure. Some of the features of such mechanisms and possible locomotion modes are discussed with relevant experimental performances. The applicability of such serpentine structures adapting to different environmental situations and locomotion requirements, is also presented using GAâ€based shape transition planner.
Â¢ T. Kamegawa, F. Matsuno, and R. Chatterjee, Proposition of twisting mode of locomotion and GA based motion planning for transition of locomotion modes of 3-dimensional snake-like robot, in Proc. IEEE Int. Conf. Robotics and Automation, 2002, vol.2, pp. 1507-1512.
Â¢ http://www.Serpentine Search Robots.com
Â¢ S. Hirose, Biologically Inspired Robots (Snake-like Locomotors and Manipulator). London, U.K.: Oxford Univ. Press, 1993.
I extend my sincere thanks to Prof. P.V.Abdul Hameed, Head of the Department for providing me with the guidance and facilities for the Seminar.
I express my sincere gratitude to Seminar coordinator
Mr. Manoj K, Staff in charge, for his cooperation and guidance for preparing and presenting this seminars.
I also extend my sincere thanks to all other faculty members of Electronics and Communication Department and my friends for their support and encouragement.
Â¢ INTRODUCTION 1
Â¢ RESCUE ROBOTS 2
Â¢ Constraints on Robotic Rescue Devices
Â¢ SERPENTINE RESCUE ROBOTS:
LEADING APPROACHES 6
Â¢ Sensor-Based Online Path Planning
Â¢ Local map building
Â¢ MDT- Based exploratory path planning methodology
Â¢ Serpentine gaits of the search robot
Â¢ Simulation Results
Â¢ DEVELOPMENT OF THE PROTOTYPE MECHANISM 14
Â¢ Twisting Mode of Locomotion
Â¢ Wheeled Locomotion
Â¢ A GA-Based Planning of Shape Transition
Â¢ OTHER APPLICATIONS 22
Â¢ ADVANTAGES 23
Â¢ DISADVANTAGES 25
Â¢ CONCLUSION 26
Â¢ REFERENCES 27