Abstract: This paper presents the design, development and characterization of contractile water jet thruster (CWJT) for mini underwater robot. Instead of electric motor, this CWJT utilizes the Ionic Polymer Metal Composite (IPMC) as the actuator to generate the water jet. The main focus of this paper is to analyze the conceptual design of the proposed CWJT which would determine the thrust force value, jet flow behavior and actuator’s stress. Those thrust force and jet flow studies were carried out using Matlab/Simscape simulation software. The actuator stress had been analyzed using COSMOS simulation software. The results showed that there was no significant change for jet velocity at variable cross sectional nozzle area. However, a significant change was detected for jet velocity at different nozzle cross sectional area ratio which was up to 37%. The generated thrust force has proportional relation to the nozzle cross sectional area.
Abstract: This paper discusses an artificial mind model and its
applications. The mind model is based on some theories which assert
that emotion is an important function in human decision making. An
artificial mind model with emotion is built, and the model is applied to
action selection of autonomous agents. In three examples, the agents
interact with humans and their environments. The examples show the
proposed model effectively work in both virtual agents and real robots.
Abstract: Robotic system is an important area in artificial intelligence that aims at developing the performance techniques of the robot and making it more efficient and more effective in choosing its correct behavior. In this paper the distributed learning classifier system is used for designing a simulated control system for robot to perform complex behaviors. A set of enhanced approaches that support default hierarchies formation is suggested and compared with each other in order to make the simulated robot more effective in mapping the input to the correct output behavior.
Abstract: This paper explores an application of an adaptive learning mechanism for robots based on the natural immune system. Most of the research carried out so far are based either on the innate or adaptive characteristics of the immune system, we present a combination of these to achieve behavior arbitration wherein a robot learns to detect vulnerable areas of a track and adapts to the required speed over such portions. The test bed comprises of two Lego robots deployed simultaneously on two predefined near concentric tracks with the outer robot capable of helping the inner one when it misaligns. The helper robot works in a damage-control mode by realigning itself to guide the other robot back onto its track. The panic-stricken robot records the conditions under which it was misaligned and learns to detect and adapt under similar conditions thereby making the overall system immune to such failures.
Abstract: Both the minimum energy consumption and
smoothness, which is quantified as a function of jerk, are generally
needed in many dynamic systems such as the automobile and the
pick-and-place robot manipulator that handles fragile equipments.
Nevertheless, many researchers come up with either solely
concerning on the minimum energy consumption or minimum jerk
trajectory. This research paper proposes a simple yet very interesting
relationship between the minimum direct and indirect jerks
approaches in designing the time-dependent system yielding an
alternative optimal solution. Extremal solutions for the cost functions
of direct and indirect jerks are found using the dynamic optimization
methods together with the numerical approximation. This is to allow
us to simulate and compare visually and statistically the time history
of control inputs employed by minimum direct and indirect jerk
designs. By considering minimum indirect jerk problem, the
numerical solution becomes much easier and yields to the similar
results as minimum direct jerk problem.
Abstract: Currently is characterized production engineering
together with the integration of industrial automation and robotics
such very quick view of to manufacture the products. The production
range is continuously changing, expanding and producers have to be
flexible in this regard. It means that need to offer production
possibilities, which can respond to the quick change. Engineering
product development is focused on supporting CAD software, such
systems are mainly used for product design. That manufacturers are
competitive, it should be kept procured machines made available
capable of responding to output flexibility. In response to that
problem is the development of flexible manufacturing systems,
consisting of various automated systems. The integration of flexible
manufacturing systems and subunits together with product design and
of engineering is a possible solution for this issue. Integration is
possible through the implementation of CIM systems. Such a solution
and finding a hyphen between CAD and procurement system ICIM
3000 from Festo Co. is engaged in the research project and this
contribution. This can be designed the products in CAD systems and
watch the manufacturing process from order to shipping by the
development of methods and processes of integration, This can be
modeled in CAD systems products and watch the manufacturing
process from order to shipping to develop methods and processes of
integration, which will improve support for product design
parameters by monitoring of the production process, by creating of
programs for production using the CAD and therefore accelerates the
a total of process from design to implementation.
Abstract: A robot simulator was developed to measure and
investigate the performance of a robot navigation system based on
the relative position of the robot with respect to random obstacles in
any two dimensional environment. The presented simulator focuses
on investigating the ability of a fuzzy-neural system for object
avoidance. A navigation algorithm is proposed and used to allow
random navigation of a robot among obstacles when the robot faces
an obstacle in the environment. The main features of this simulator
can be used for evaluating the performance of any system that can
provide the position of the robot with respect to obstacles in the
environment. This allows a robot developer to investigate and
analyze the performance of a robot without implementing the
physical robot.
Abstract: This paper presents an Extended Kaman Filter
implementation of a single-camera Visual Simultaneous Localization
and Mapping algorithm, a novel algorithm for simultaneous
localization and mapping problem widely studied in mobile robotics
field. The algorithm is vision and odometry-based, The odometry
data is incremental, and therefore it will accumulate error over time,
since the robot may slip or may be lifted, consequently if the
odometry is used alone we can not accurately estimate the robot
position, in this paper we show that a combination of odometry and
visual landmark via the extended Kalman filter can improve the robot
position estimate. We use a Pioneer II robot and motorized pan tilt
camera models to implement the algorithm.
Abstract: This paper proposes a balance control scheme for a biped robot to trace an arbitrary path using image information. While moving, it estimates the zero moment point(ZMP) of the biped robot in the next step using a Kalman filter and renders an appropriate balanced pose of the robot. The ZMP can be calculated from the robot's pose, which is measured from the reference object image acquired by a CCD camera on the robot's head. For simplifying the kinematical model, the coordinates systems of individual joints of each leg are aligned and the robot motion is approximated as an inverted pendulum so that a simple linear dynamics, 3D-LIPM(3D-Linear Inverted Pendulum Mode) can be applied. The efficiency of the proposed algorithm has been proven by the experiments performed on unknown trajectory.
Abstract: This research paper designs a unique motion planner
of multiple platoons of nonholonomic car-like robots as a feasible
solution to the lane changing/merging maneuvers. The decentralized
planner with a leaderless approach and a path-guidance principle
derived from the Lyapunov-based control scheme generates collision
free avoidance and safe merging maneuvers from multiple lanes to a
single lane by deploying a split/merge strategy. The fixed obstacles
are the markings and boundaries of the road lanes, while the moving
obstacles are the robots themselves. Real and virtual road lane
markings and the boundaries of road lanes are incorporated into a
workspace to achieve the desired formation and configuration of the
robots. Convergence of the robots to goal configurations and the
repulsion of the robots from specified obstacles are achieved by
suitable attractive and repulsive potential field functions,
respectively. The results can be viewed as a significant contribution
to the avoidance algorithm of the intelligent vehicle systems (IVS).
Computer simulations highlight the effectiveness of the split/merge
strategy and the acceleration-based controllers.
Abstract: Conceptualization strengthens intelligent systems in generalization skill, effective knowledge representation, real-time inference, and managing uncertain and indefinite situations in addition to facilitating knowledge communication for learning agents situated in real world. Concept learning introduces a way of abstraction by which the continuous state is formed as entities called concepts which are connected to the action space and thus, they illustrate somehow the complex action space. Of computational concept learning approaches, action-based conceptualization is favored because of its simplicity and mirror neuron foundations in neuroscience. In this paper, a new biologically inspired concept learning approach based on the probabilistic framework is proposed. This approach exploits and extends the mirror neuron-s role in conceptualization for a reinforcement learning agent in nondeterministic environments. In the proposed method, instead of building a huge numerical knowledge, the concepts are learnt gradually from rewards through interaction with the environment. Moreover the probabilistic formation of the concepts is employed to deal with uncertain and dynamic nature of real problems in addition to the ability of generalization. These characteristics as a whole distinguish the proposed learning algorithm from both a pure classification algorithm and typical reinforcement learning. Simulation results show advantages of the proposed framework in terms of convergence speed as well as generalization and asymptotic behavior because of utilizing both success and failures attempts through received rewards. Experimental results, on the other hand, show the applicability and effectiveness of the proposed method in continuous and noisy environments for a real robotic task such as maze as well as the benefits of implementing an incremental learning scenario in artificial agents.
Abstract: In this paper, we study the formation control problem
for car-like mobile robots. A team of nonholonomic mobile robots navigate in a terrain with obstacles, while maintaining a desired
formation, using a leader-following strategy. A set of artificial potential field functions is proposed using the direct Lyapunov
method for the avoidance of obstacles and attraction to their designated targets. The effectiveness of the proposed control laws to verify the feasibility of the model is demonstrated through computer simulations
Abstract: In this work a software simulation model has been
proposed for two driven wheels mobile robot path planning; that can
navigate in dynamic environment with static distributed obstacles.
The work involves utilizing Bezier curve method in a proposed N
order matrix form; for engineering the mobile robot path. The Bezier
curve drawbacks in this field have been diagnosed. Two directions:
Up and Right function has been proposed; Probability Recursive
Function (PRF) to overcome those drawbacks.
PRF functionality has been developed through a proposed;
obstacle detection function, optimization function which has the
capability of prediction the optimum path without comparison
between all feasible paths, and N order Bezier curve function that
ensures the drawing of the obtained path.
The simulation results that have been taken showed; the mobile
robot travels successfully from starting point and reaching its goal
point. All obstacles that are located in its way have been avoided.
This navigation is being done successfully using the proposed PRF
techniques.
Abstract: Augmented Reality (AR) shows great promises for
its usage as a tool for simulation and verification of design proposal
of new technological systems. Main advantage of augmented reality
application usage is possibility of creation and simulation of new
technological unit before its realization. This may contribute to
increasing of safety and ergonomics and decreasing of economical
aspects of new proposed unit. Virtual model of proposed workcell
could reveal hidden errors which elimination in later stage of new
workcell creation should cause great difficulties. Paper describes
process of such virtual model creation and possibilities of its
simulation and verification by augmented reality tools.
Abstract: This paper suggests a calibration method to reduce
errors occurring due to mobile robot sliding during location estimation
using the Dead-reckoning. Due to sliding of the mobile robot caused
between its wheels and the road surface while on free run, location
estimation can be erroneous. Sliding especially occurs during
cornering of mobile robot. Therefore, in order to reduce these frequent
sliding errors in cornering, we calibrated the mobile robot-s heading
values using a vision camera and templates of the ceiling.
Abstract: High redundancy and strong uncertainty are two main characteristics for underwater robotic manipulators with unlimited workspace and mobility, but they also make the motion planning and control difficult and complex. In order to setup the groundwork for the research on control schemes, the mathematical representation is built by using the Denavit-Hartenberg (D-H) method [9]&[12]; in addition to the geometry of the manipulator which was studied for establishing the direct and inverse kinematics. Then, the dynamic model is developed and used by employing the Lagrange theorem. Furthermore, derivation and computer simulation is accomplished using the MATLAB environment. The result obtained is compared with mechanical system dynamics analysis software, ADAMS. In addition, the creation of intelligent artificial skin using Interlink Force Sensing ResistorTM technology is presented as groundwork for future work
Abstract: Human perceives color in categories, which may be
identified using color name such as red, blue, etc. The categorization
is unique for each human being. However despite the individual
differences, the categorization is shared among members in society.
This allows communication among them, especially when using
color name. Sociable robot, to live coexist with human and become
part of human society, must also have the shared color
categorization, which can be achieved through learning. Many
works have been done to enable computer, as brain of robot, to learn
color categorization. Most of them rely on modeling of human color
perception and mathematical complexities. Differently, in this work,
the computer learns color categorization through interaction with
humans. This work aims at developing the innate ability of the
computer to learn the human-like color categorization. It focuses on
the representation of color categorization and how it is built and
developed without much mathematical complexity.
Abstract: We present design, fabrication, and characterization of
a small (12 mm × 12 mm × 8 mm) movable railway vehicle for sensor
carrying. The miniature railway vehicle (MRV) was mainly composed
of a vibrational structure and three legs. A railway was designed and
fabricated to power and guide the MRV. It also transmits the sensed
data from the MRV to the signal processing unit. The MRV with legs
on the railway was moving due to its high-frequency vibration. A
model was derived to describe the motion. Besides, FEM simulations
were performed to design the legs. Then, the MRV and the railway
were fabricated by precision machining. Finally, an infrared sensor
was carried and tested. The result shows that the MRV without loading
was moving along the railway and its maximum speed was 12.2 mm/s.
Moreover, the testing signal was sensed by the MRV.
Abstract: In this paper, the bio-mechanical analysis of human joints is carried out and the study is extended to the robot manipulator. This study will first focus on the kinematics of human arm which include the movement of each joint in shoulder, wrist, elbow and finger complexes. Those analyses are then extended to the design of a human robot manipulator. A simulator is built for Direct Kinematics and Inverse Kinematics of human arm. In the simulation of Direct Kinematics, the human joint angles can be inserted, while the position and orientation of each finger tips (end-effector) are shown. Inverse Kinematics does the reverse of the Direct Kinematics. Based on previous materials obtained from kinematics analysis, the human manipulator joints can be designed to follow prescribed position trajectories.
Abstract: An intuitive user interface for the teleoperation of mobile rescue robots is one key feature for a successful exploration of inaccessible and no-go areas. Therefore, we have developed a novel framework to embed a flexible and modular user interface into a complete 3-D virtual reality simulation system. Our approach is based on a client-server architecture to allow for a collaborative control of the rescue robot together with multiple clients on demand. Further, it is important that the user interface is not restricted to any specific type of mobile robot. Therefore, our flexible approach allows for the operation of different robot types with a consistent concept and user interface. In laboratory tests, we have evaluated the validity and effectiveness of our approach with the help of two different robot platforms and several input devices. As a result, an untrained person can intuitively teleoperate both robots without needing a familiarization time when changing the operating robot.