Abstract: Generally speaking, the mobile robot is capable of
sensing its surrounding environment, interpreting the sensed
information to obtain the knowledge of its location and the
environment, planning a real-time trajectory to reach the object. In
this process, the issue of obstacle avoidance is a fundamental topic to
be challenged. Thus, an adaptive path-planning control scheme is
designed without detailed environmental information, large memory
size and heavy computation burden in this study for the obstacle
avoidance of a mobile robot. In this scheme, the robot can gradually
approach its object according to the motion tracking mode, obstacle
avoidance mode, self-rotation mode, and robot state selection. The
effectiveness of the proposed adaptive path-planning control scheme
is verified by numerical simulations of a differential-driving mobile
robot under the possible occurrence of obstacle shapes.
Abstract: Designing a simulated system and training it to optimize its tasks in simulated environment helps the designers to avoid problems that may appear when designing the system directly in real world. These problems are: time consuming, high cost, high errors percentage and low efficiency and accuracy of the system. The proposed system will investigate and improve the efficiency and accuracy of a simulated robot to choose correct behavior to perform its task. In this paper, machine learning, which uses genetic algorithm, is adopted. This type of machine learning is called genetic-based machine learning in which a distributed classifier system is used to improve the efficiency and accuracy of the robot. Consequently, it helps the robot to achieve optimal action.
Abstract: The research on two-wheeled inverted pendulum (TWIP) mobile robots or commonly known as balancing robots have gained momentum over the last decade in a number of robotic laboratories around the world. This paper describes the hardware design of such a robot. The objective of the design is to develop a TWIP mobile robot as well as MATLAB interfacing configuration to be used as flexible platform comprises of embedded unstable linear plant intended for research and teaching purposes. Issues such as selection of actuators and sensors, signal processing units, MATLAB Real Time Workshop coding, modeling and control scheme will be addressed and discussed. The system is then tested using a wellknown state feedback controller to verify its functionality.
Abstract: In this contribution is presented a complex design of
individual objects identification in the workplace of intelligent
assembly cell. Intelligent assembly cell is situated at Institute of
Manufacturing Systems and Applied Mechanics and is used for
pneumatic actuator assembly. Pneumatic actuator components are
pneumatic roller, cover, piston and spring. Two identification objects
alternatives for assembly are designed in the workplace of industrial
robot. In the contribution is evaluated and selected suitable
alternative for identification – 2D codes reader. The complex design
of individual object identification is going out of intelligent
manufacturing systems knowledge.
Intelligent assembly and manufacturing systems as systems of
new generation are gradually loaded in to the mechanical production,
when they are removeing human operation out of production process
and they also short production times.
Abstract: This paper proposes a robot able to climb Columns.
This robot is not dependent on the diameter and material of the
columns. Some climbing robots have been designed up to now but
Koala robot was designed and fabricated for climbing columns
exclusively. Simple kinematics of climbing in the nature inspired us
to design this robot. We used two linear mechanisms to grip the
column. The gripper consists of a DC motor and a power screw
mechanism with a linear bushing as a guide. This mechanism
provides enough force to grip the column. In addition we needed an
actuator for climbing the column; hence, two pneumatic jacks were
used. All the mechanical parts were designed according to the
exerted forces and operational condition. The prototype can be
simply installed and controlled on the column by an inexperienced
operator. This robot is intended for inspection and surveillance of
pipes in oil industries and power poles in electric industries.
Abstract: This paper describes various stages of design and prototyping of a modular robot for use in various industrial applications. The major goal of current research has been to design and make different robotic joints at low cost capable of being assembled together in any given order for achieving various robot configurations. Five different types of joins were designed and manufactured where extensive research has been carried out on the design of each joint in order to achieve optimal strength, size, modularity, and price. This paper presents various stages of research and development undertaken to engineer these joints that include material selection, manufacturing, and strength analysis. The outcome of this research addresses the birth of a new generation of modular industrial robots with a wider range of applications and greater efficiency.
Abstract: Recently there has been a growing interest in the field
of bio-mimetic robots that resemble the behaviors of an insect or an
aquatic animal, among many others. One of various bio-mimetic robot
applications is to explore pipelines, spotting any troubled areas or
malfunctions and reporting its data. Moreover, the robot is able to
prepare for and react to any abnormal routes in the pipeline. Special
types of mobile robots are necessary for the pipeline monitoring tasks.
In order to move effectively along a pipeline, the robot-s movement
will resemble that of insects or crawling animals. When situated in
massive pipelines with complex routes, the robot places fixed sensors
in several important spots in order to complete its monitoring. This
monitoring task is to prevent a major system failure by preemptively
recognizing any minor or partial malfunctions. Areas uncovered by
fixed sensors are usually impossible to provide real-time observation
and examination, and thus are dependent on periodical offline
monitoring. This paper proposes a monitoring system that is able to
monitor the entire area of pipelines–with and without fixed
sensors–by using the bio-mimetic robot.
Abstract: There has been a growing interest in the field of
bio-mimetic robots that resemble the shape of an insect or an aquatic
animal, among many others. One bio-mimetic robot serves the
purpose of exploring pipelines, spotting any troubled areas or
malfunctions and reporting its data. Moreover, the robot is able to
prepare for and react to any abnormal routes in the pipeline. In order
to move effectively inside a pipeline, the robot-s movement will
resemble that of a lizard. When situated in massive pipelines with
complex routes, the robot places fixed sensors in several important
spots in order to complete its monitoring. This monitoring task is to
prevent a major system failure by preemptively recognizing any minor
or partial malfunctions. Areas uncovered by fixed sensors are usually
impossible to provide real-time observation and examination, and thus
are dependant on periodical offline monitoring. This paper provides
the Monitoring System that is able to monitor the entire area of
pipelines–with and without fixed sensors–by using the bio-mimetic
robot.
Abstract: For stable bipedal gait generation on the level floor,
efficient restoring of mechanical energy lost by heel collision at
the ground is necessary. Parametric excitation principle is one of
the solutions. We dealt with the robot-s total center of mass as
an inverted pendulum to consider the total dynamics of the robot.
Parametrically excited walking requires the use of continuous target
trajectory that is close to discontinuous optimal trajectory. In this
paper, we proposed the new target trajectory based on a position
in the walking direction. We surveyed relations between walking
performance and the parameters that form the target trajectory via
numerical simulations. As a result, it was found that our target
trajectory has the similar characteristics of a parametrically excited
inverted pendulum.
Abstract: This paper presents a new type of mechanism and trajectory planning strategy for bipedal walking robot. The newly designed mechanism is able to improve the performance of bipedal walking robot in terms of energy efficiency and weight reduction by utilizing minimum number of actuators. The usage of parallelogram mechanism eliminates the needs of having an extra actuator at the knee joint. This mechanism works together with the joint space trajectory planning in order to realize straight legged walking which cannot be achieved by conventional inverse kinematics trajectory planning due to the singularity. The effectiveness of the proposed strategy is confirmed by computer simulation results.
Abstract: Inverse kinematics analysis plays an important role in developing a robot manipulator. But it is not too easy to derive the inverse kinematic equation of a robot manipulator especially robot manipulator which has numerous degree of freedom. This paper describes an application of Artificial Neural Network for modeling the inverse kinematics equation of a robot manipulator. In this case, the robot has three degree of freedoms and the robot was implemented for drilling a printed circuit board. The artificial neural network architecture used for modeling is a multilayer perceptron networks with steepest descent backpropagation training algorithm. The designed artificial neural network has 2 inputs, 2 outputs and varies in number of hidden layer. Experiments were done in variation of number of hidden layer and learning rate. Experimental results show that the best architecture of artificial neural network used for modeling inverse kinematics of is multilayer perceptron with 1 hidden layer and 38 neurons per hidden layer. This network resulted a RMSE value of 0.01474.