Abstract — Development of an obstacleavoidingrobot model is required as a fundamental step towards a bigger goal, for example development of an autonomous vehicle. An obstacleavoidingrobot uses a proximity sensor module, besides other parts. In this case, this robot uses a proximity sensor developed by ourselves. The robot is controlled by a program that is embedded into a microcontroller. The logics produced by the microcontroller are further processed by an interface module, in this case, also developed by ourselves. The interface module translates microcontroller’s logics into voltage and current that can practically drive the two motors. This article provides a report on the project activity, consisting of summary of the design, summary of the development process and report on the running test of the robot. Following the test and program fine-tuning, it has been proven that the robot model operated well just as programmed.
There have been many accounts of user-configurable automated devices and even automata resembling animals and humans, designed primarily as entertainment since ages. A robot(1) is a modern day invention, a mechanical or virtual artificial agent, usually an electro-mechanical machine that is guided by a computer program or electronic circuitry. Robots can be autonomous or semi-autonomous and range from humanoids. By mimicking a lifelike appearance or automating movements, a robot may convey a sense of intelligence or thought of its own. The evolution robots is synchronised with the development of Science and Technology, be it in the field of Electronics, Computer Science , Nano Technology etc. Electronics evolved into the driving force of development with the advent of the first electronic autonomous robots created by William Grey Walter in Bristol, England in 1948. The first digital and programmable robot was invented by George Devol in 1954 and was named the Unimate. Obstacle avoidance method for robots is modern concept, where the robots are programmed to sense the obstacle by using different programmes like AVR or Adriano etc. To overcome the presence of obstacles or forbidden regions that restrict the movement of the robot and determine an optional path that will is the motto of the project.
The track which the Autobot needs to follow should be pre-fed into the built in microcontroller, i.e., the distance and the angle of the final point from the initial point. If the Autobot needs to travel in a curved path the required equation of the curve needs to be provided. Once the equation is determined, the instantaneous coordinates of the center of the Autobot are fed into the equation over which the Autobot has to travel. The micro-controller calculates the position of the center of the Autobot on the basis of the information provided by the left and right wheel encoders and feeds these instantaneous co-ordinates to the desired equation of travel. This helps to monitor the position of the center of the robot. A PID controller can be used to help the Autobot move over the desired equation. If the Autobot deviates from the equation it was supposed to move over, an error signal would be generated. The constants Kp,Ki,Kd would be calculated by the micro-controller. If the Autobot, drifts to right of its desired path the PID controller would try to minimize the error by trying to move the Autobot in the left direction. In such a condition the micro-controller needs to vary the speed of the Left and Right motors in such a way that the Autobot drifts left till the center is not following the required equation of travel.
Sturgeon's work, a commutator-type direct-current electric motor made with the intention of commercial use was built by the American Thomas Davenport and patented in 1837. Although several of these motors were built and used to operate equipment such as a printing press, due to the high cost of primary battery power, the motors were commercially unsuccessful and Davenport went bankrupt. Several inventors followed Sturgeon in the development of DC motors but all encountered the same cost issues with primary battery power. No electricity distribution had been developed at the time. Like Sturgeon's motor, there was no practical commercial market for these motors.
available information effectively. For many practical problems, however, an important portion of information comes from human experts which is usually not precise and is represented by fuzzy terms like small, large, not very new, and so on. In addition, in controlling complex systems such as mobile robot navigation, we are faced with the problem of inadequate modeling of the systems, a large quantity of uncertain sensory measurements that are difficult to interpret accurately, and lacking efficient computations of control actions to achieve a desired performance of the systems. This means that, effective control of mobile robots and their associated sensors demands the synthesis and satisfaction of several complex constraints and objectives in real-time, particularly in unstructured, unknown, or dynamic environments such as those typically encountered by outdoor mobile robots. The publication of Professor Zadeh (Zadeh, 1 965) on fuzzy sets has spurred a great interest in the development of fuzzy logic controllers as an alternative to existing advanced model-based controllers for controlling such
decision. The movement of obstacleavoidingrobot cannot be controlled. Considering this factor line follower robot has more useful applications. This conventional line follower robot can be made smart and intelligent by giving it the ability to detect obstacles. This improves the working of the line follower robot, because in any work environment obstacles are common, so if the line follower is not able to detect any obstacles on its path it will collide with it and will be severely damaged. Adding the features of obstacleavoidingrobot to a traditional line follower robot prevents any damage to the robot. This intelligent robot can also be installed for health care management in hospitals, which decreases the human effort in monitoring patients and delivery things or medicines. The workers can be used for other tasks instead of transporting goods from one place to other which can be carried out with this smart and intelligent line follower robot.
12 21 4 1;0;0 Stable The robot's effectiveness in avoiding obstacles is affected by the number of hidden layers. This is related to the number of hidden layers used the more number of hiden layer the better the robot in moving. But in the experi- ments that have been done by using some hid- den layer with different amounts obtained hid- den layer with the number of usage 20 hidden layer. It is said to be effective testing in the movement of the robot is smoother in moving as well as more stable.
Advances in robot replanning have made possible the devel- opment of serious autonomous vehicles that may be used to explore other planets, gather data in areas considered too dan- gerous for humans, and even park themselves without human involvement. Notable among these advances is the marriage of incremental search algorithms with sophisticated search heuristics that exploit learned terrain information to narrow the search space and thereby speed up the replanning process. The D* Lite algorithm [3, 4] represents the state-of-the-art in such replanning algorithm development. A descendant of the A* and D* [1, 2] algorithms, D* Lite is easily implemented and its “experimental properties show that D* Lite is at least as efficient as D*.” It has been used successfully in a variety of roles.
The distance between near objects and the robot is used for the situation recognition. Far distanced objects should be ignored because an approach of these is uncertain. If an object is too close, a reaction, for example an avoiding maneuver, should be performed. Hence, only objects within a certain distance-window are relevant for learning. We mapped this window on image regions, as it can be seen in Figure 6. The upper part is ignored for processing, based on the assumption that far objects are located there. Close objects can be found on the bottom part of the image. Therefore, the robot stops as soon as the object contours overlap this lower part. However, the first assumption fails sometimes, for example concerning nearby tall objects as depicted in Figure 6 on the right. In this case available object information is thrown away.
Chan Zhi Wei and Muhammad Nasiruddin Mahyuddin studied about Neuro-Fuzzy Algorithm for Obstacle Avoidance Mission of a Mobile Robot Using FPGA discussed that the designed obstacle avoidance program for mobile robot that incorporates a neuro-fuzzy algorithm using Altera Field Programmable Gate Array (FPGA) development board. Field Programmable Gate Array (FPGA) circuits provide suitable platform in realizing complex hardware system as well as implementing data intensive algorithm computation. The ability to easily reconfigure FPGA makes the design less expensive than pre-designed hardware. These features bring convenience to incorporating an artificial intelligence- based-program for mobile robot navigation and obstacle avoidance task or mission .
Abstract: Hyper-redundant snake-like serial robots is one area where in there is a lot of research going on due to their application in search and rescue operation during disaster relief in highly risky environment and recently in the areas of therapeutical applications. A major contributing feature of these robots is the presence of a many number of redundant actuated joints and the associated well-known challenge of motion planning. This problem is even more severe in the presence of obstacles. Obstacle avoidance for point bodies, non-redundant serial robots with a few links and joints and wheeled mobile robots has been extensively studied and several mature implementations are available. However, obstacle avoidance for hyper- redundant snake-like robots and other extended articulated bodies is less studied and is still evolving. This paper shows a novel enhancement calculation, determined utilizing analytics of variety, for the movement arranging of a hyper-excess robot where the movement of one end (head) is a discretionary wanted way. The calculation registers the movement of the considerable number of joints in the hyper-repetitive robot in a way to such an extent that every one of its connections keep away from all snags present in the earth. The calculation is simply geometric in nature and it is indicated that the movement in free space and in the region of deterrents has all the earmarks of being progressively characteristic. The paper exhibits the general hypothetical improvement and numerical recreations results. It additionally displays approving outcomes from tries different things with a 12-degree-of-freedom planar hyper-repetitive robot moving in a known snag field.
7 Chee et all.  presented a two-layer fuzzy inference system in which the first layer fuses the sensor readings. The left and right clearances of the robot were found as outputs of the first-layered fuzzy system. The outputs of the first layer together with the goal direction are used as the inputs of the second-layer. Eventually, the final outputsof the controller are the linear velocity and the turning rate of the robot. The second-stage fuzzy inference system employs the collision avoiding, obstacle following and goal tracking behaviours to achieve robust navigation in unknown environments. Dadios and Maravillas proposed and implemented a fuzzy control approach for cooperative soccer micro robots. A planner generates a path to the destination and fuzzy logic control the robot’s heading direction to avoid obstacles and other robots while the dynamic position of obstacles, ball and robots are considered .
Abstract. Obstacle recognition is remain a challenge especially for the inspection robot of high voltage transmission line under varying degrees of illumination environments. This paper proposes an effective method to overcome the influence of low illumination. The proposed method firstly uses homomorphic filtering to attenuate high frequency illumination component; it then applies the Hu moment to extract obstacle features. The extensive experiments show that the proposed method is superior to four state-of-the-art algorithms, and achieves 88%, 87%, 90% obstacles recognition accuracy rate on shockproof hammer, suspension clamp and insulator string databases, respectively. Compared with other peer algorithms, homomorphic filtering has strong anti-illumination capability and the algorithm based on moment feature has higher recognition rate. The research improved the robustness of vision system of line-patrolling robot to image recognition, and promotes the safe, efficient, intelligent and sustainable development of power industry.
The experiments took place in Webots, a robot simulator that provides a complete development environment to model, program, simulate and validate robotic researches. Because Nao robot has some stability issues the simulation and validation in a VE is a responsible approach in order to protect the real robot from bumping against surrounding objects or falling during trials. Our experiments consisted in several scenarios, where robot had to walk in a virtual apartment room and avoid objects in his path. Objects in the room had different sizes and shapes. In fig. 6 and fig.7 we present the trajectories of the robot where target position was set in right side and left side of the room. Nao robot is able to avoid all objects in the virtual environment and even able to squeeze between two objects in the room, as we can see in fig.7. We have also tested the robot walking along the wall having to make a decision when came across corners or narrow gaps.
Mobile robots feature some kind of damage avoidance by avoiding collision, ranging from basic algorithms that detect an blocks to avoid a collision, using some basic program code, that initialize the robot to detect blocks. The program code is easy, since it is involved simple obstacle detection as well as some kind of obstacle distance measurement to avoid collision. Once block is determined, the obstacle avoidance program needs to direct the robot around the block and halt motion and direct robot to desired direction. In this paper the redirecting algorithm makes the robot does not have to stop in front the block and find its path. Hence the robots may overcome problems during path finding, it can direct robot during its operation avoiding the bumping with walls.
The primary objective of this book is to provide references for dissemination and discussion of the topics that have been presented in the conference. This volume is unique in that it includes work related to Electrical Engineering, Technology and Information towards their sustainable development. Engineers, researchers as well as lecturers from universities and professionals in industry and government will gain valuable insights into interdisciplinary solutions in the ﬁ eld of Electrical Systems, Technology and Information, and its applications.
Main aim of this paperwork is to study development of the obstacleavoiding spy robot, which can be operated manually as per the operator wants to take control of the robot himself, it also can be autonomous in its actions while intelligently moving itself by detecting the obstacles in front of it by the help of the obstacle detectable circuit. The robot is in form of a vehicle mounted with a web cam, which acquires and sends video as per the robots eye view to a TV or PC via a TV tuner card. The microcontroller chip ATMEGA 328 present on the microcontroller board ARDUINO controls the movements of the robot. In manual operating conditions the user will have a radio transmitter (tx) via which the user will send signal to the radio receiver (rx) present inside the robot which accordingly will pass on the signal to the microcontroller board, and as per the coding of the signal signatures burnt inside the microcontroller chip the robot will complete its movements. In Autonomous operating conditions the user will have no control on the robot that is the robot cannot be operated via any external controls, it will only function as per the data received from the obstacle detection circuits to the microcontroller which will make the robot motors move accordingly as per the code written in it. The idea is to make a robot to tackle the hostage situations & cope up with the worst conditions, which can be quiet a matter of risk to be handled by human being.
Abstract— The paper presents a human following and an obstacleavoiding algorithm for the Bot that provides a service to a marathoner while training. For its working, the Bot shold have the abilities of following a human and dynamically avoid the variable positioning obstacles in an unlevelled outdoor surroundings. The Bot detects a human by a transceiver model , speed is controlled using PWM signal concept and the direction is controlled using sensors. To avoid moving obstacles while following a running person, there is a defined definite radius of each obstacle using the relative velocity between the Bot and an obstacle. For easily avoiding obstacles without collision, a dynamic obstacleavoiding algorithm for the Bot is implemented, which directly employs a real-time position between the Bot and it follows the shortest path around the obstacle to avoid it. We verified the feasibility of these algorithms through experimentation in different outdoor environments.
Abstract – In today’s world working on robots is growing fast. In this field controlling robots with remotes is a complicated part as there is a chance of confusion by the user. Instead, we can use the concept of gestures i.e. we can control the movement of robot using chronos watch and make hand movements. The users have to wear a chronos watch. The accelerometer present in chromos watch will record hand movement in specific direction and commands the robot to move in that respective direction. The robot also consists of a camera along with the watch and is connected wirelessly via radio wave which enables to interact in a more friendly way. It can also sense the obstacles and responds accordingly. The main objective is to make a simple and cheap robot which could be of help in many purposes.
Industrial robots are only able to carry out their tasks in their work-space. Work-space means the maximum point of reach for the end-effector of an industrial robot. Usually, the work-space of industrial robots exists in 3 dimensional spaces. They also have a different work-space according to the 2 type of motion which are linear and rotate. The first 3 joint at the robot or called 3 major axes combination contribute the various shape of work-space and its can determine the position of wrist. Therefore, statements below will describe the 4 basic types of movement of industrial robot .