Configuration of ARDev was unable to perform at runtime. It was necessary to terminate the program and reinitialize it in order to change any settings. This tool should ideally be run constantly helping to avoid the potential loss of time and important data.
In order to provide configuration and runtime control of ARDev a graphical user interface library was added. The Library AntTweakBar was chosen as a lightweight option. The main GUI window for ARDev is small, and provides buttons to open further windows and also provides control over player connections, Environment and Data, display information regarding rendered objects, environments and environments switching, and miscellaneous robot data respectively.
The Display List Window can be used to show and hide objects of interest and to change the color or transparency of rendered objects which can be very useful at runtime when rendered objects overlap and obscure each other. Some objects extended settings are provided; in the case of the grid, the minor and major grid lines can be changed quickly for less or more precision.
With the GUI addition it is now easy to change runtime settings, manipulate the environment and view the state of the system. Further configurations easily be added for any type of object using the extensible architecture. Developing robots that are mobile and interact with the real world can be a significant challenge. The available tools for a developer to understand complex robot data in a real time and useful way are limited, resulting in an extended time to find the correct solutions. The real time world is dynamic and complex and can not be easily understood from a robot’s perspective without placing the robot’s data in context with the developers world view. Visualization of actuators and sensor readings can be interpreted easily when overlaid onto an image of the real world. Any inconsistencies between real time robot data and what the developer actually can see in the real world become obvious when presented in a visual manner.
Blog about Robotics Introduction, news of the robot, information about the robot, sharing knowledge about the various kinds of robots, shared an article about robots, and others associated with the robot
Four Practices to Control Robot Design Architectures
The platforms of robot controllers development and their underlying methodologies are of great importance for IT and laboratories society, because there is an increasing interest in future service robotics. Such platforms help developers in many of their activities such as modeling, programming, model analysis, test and simulation and should take into account preoccupations like the reuse of software pieces and the modularity of control architectures as they correspond to two major issues.
The aim of this platform development is to provide a robot controller development methodology and its dedicated tools, in order to help developers overcoming problems during all steps of the design process. So, we investigate on the creation of a software paradigm that deals specifically with controller development preoccupations. We identified four main different practices in control architecture design approaches that must be considered.
Firstly, is the structuring of the control activities. There are different approaches, contains decomposing the control architecture into hierarchical layers. Each layer within the robot controller has a ‘decision making system”, as each layer only ensures part of the control from low level control to planning.
Secondly, id the decomposition of the control architecture into subsystem that incorporate the specific parts control of a robotic system. This practice is reified in IDEA agents architecture and Chimera development methodology. This organizational view is orthogonal to the hierarchical one: each subsystem can incorporate both reactive and long term decision making activities and so can be layered itself.
Thirdly, is to separate, in architecture description, the robot operative portion description from the control and decision making one. This practice is often adopted at implementation phase, except in specific architectures like CLARATY, which in the real world description is made by means of objects hierarchies.
Fourth, is to use notations to describe the controller’s parts and to formalize their interactions. Model based specifications are coupled with techniques of formal analysis in order to follow a quality oriented of design process.
The aim of this platform development is to provide a robot controller development methodology and its dedicated tools, in order to help developers overcoming problems during all steps of the design process. So, we investigate on the creation of a software paradigm that deals specifically with controller development preoccupations. We identified four main different practices in control architecture design approaches that must be considered.
Firstly, is the structuring of the control activities. There are different approaches, contains decomposing the control architecture into hierarchical layers. Each layer within the robot controller has a ‘decision making system”, as each layer only ensures part of the control from low level control to planning.
Secondly, id the decomposition of the control architecture into subsystem that incorporate the specific parts control of a robotic system. This practice is reified in IDEA agents architecture and Chimera development methodology. This organizational view is orthogonal to the hierarchical one: each subsystem can incorporate both reactive and long term decision making activities and so can be layered itself.
Thirdly, is to separate, in architecture description, the robot operative portion description from the control and decision making one. This practice is often adopted at implementation phase, except in specific architectures like CLARATY, which in the real world description is made by means of objects hierarchies.
Fourth, is to use notations to describe the controller’s parts and to formalize their interactions. Model based specifications are coupled with techniques of formal analysis in order to follow a quality oriented of design process.
The Application of Augmented Reality
Developing mobile robot applications in a real world environment presents a number of challenges. The challenges are a result of the researcher developing the application often being remote from the robot, real environments are dynamic and the information provided by sensors can not be interpreted easily in real time with classical techniques. AR (Augmented Reality) provides a means to solve many of these problems placing the sensor data geographically with the robot in real time and the associated physical surrounding.
The application domains for AR are diverse and ranging from medical displays, to entertainment, to treating psychological disorders. AR has been used in to aid an operator when maneuvering a vehicle in limited or no visibility. The design of the AR system is presented discussing hardware and integration of a near scene map building algorithm. An AR system is used to aid in commissioning helicopter tasks for agriculture. Their work focusing in tracking the camera pose using natural features as markers, with results given from a mock up simulation.
It is generally agreed that it is the developer’s lack of understanding of the robot’s world view that makes it difficult to code new tasks and algorithms, debug problems in the resulting actions and commission integrated systems for real world work. The problem of understanding can be overcome with a shared perceptual space. AR provides this shared space between robots and developers enabling the developer to view he world through the robots sensors.
The ARDev (Augmented Reality Visualization Project), originally created in 2006, was designed to allow visual debugging of robot data. ARDev integrates with the open source player project, providing intuitive visualizations of player robot data. The integration into the player projects makes ARDev very accessible with easy access to existing sensors through the generic player interfaces. The AR visualization used in ARDev provides developers with a clear, visual representation of robot data, and can be used by the researcher to detect problems between the real world and the robot.
The application domains for AR are diverse and ranging from medical displays, to entertainment, to treating psychological disorders. AR has been used in to aid an operator when maneuvering a vehicle in limited or no visibility. The design of the AR system is presented discussing hardware and integration of a near scene map building algorithm. An AR system is used to aid in commissioning helicopter tasks for agriculture. Their work focusing in tracking the camera pose using natural features as markers, with results given from a mock up simulation.
It is generally agreed that it is the developer’s lack of understanding of the robot’s world view that makes it difficult to code new tasks and algorithms, debug problems in the resulting actions and commission integrated systems for real world work. The problem of understanding can be overcome with a shared perceptual space. AR provides this shared space between robots and developers enabling the developer to view he world through the robots sensors.
The ARDev (Augmented Reality Visualization Project), originally created in 2006, was designed to allow visual debugging of robot data. ARDev integrates with the open source player project, providing intuitive visualizations of player robot data. The integration into the player projects makes ARDev very accessible with easy access to existing sensors through the generic player interfaces. The AR visualization used in ARDev provides developers with a clear, visual representation of robot data, and can be used by the researcher to detect problems between the real world and the robot.
Autonomous Mental Development by Robot and Animals
How does one create the intelligent of machine? This problem has proven difficult. Scientist have taken one of three approaches over the past years, firstly, which is knowledge based, an intelligent machine in a laboratory is programmed directly to perform a given task. Secondly, learning base approach, a computer is “spoon fed” human edited sensory data while the machine is controlled by a task specific learning program. Third, is by a “genetic search”, robots have evolved through generations by the principle of survival of the fittest, mostly in a computer simulated virtual world. Although notable, none of these is powerful enough to lead to machine having the diverse, complex, and highly integrated capabilities of an adult brain, such as vision, language and speech. These traditional approaches have done as the incubator for the birth and growth of a new direction for machine intelligence: autonomous mental development.
What is autonomous mental development? With a brainlike natural or an artificial embodied system, under the control of its intrinsic developmental program develops mental capabilities through autonomous real time interactions with its environments by using its own effectors and sensors. Traditionally, a machine is not autonomous when it develops its skills, but a human is autonomous throughout its lifelong mental development.
Current advances in neuroscience illustrate this principle. For instance, if the optic nerves originating from the eyes of an animal are connected into the auditory pathway early in life, the auditory cortex gradually takes on representation that is normally found in the visual cortex. Further, the rewired animals learn successfully to perform vision tasks with the auditory cortex. This discovery advises that the cortex is governed by developmental principles that work for both auditory and visual signals. For instance, the developmental program of the monkey brain dynamically elect sensory input, according to the actual sensory signal that received, and the selection process is active throughout adulthood.
What is autonomous mental development? With a brainlike natural or an artificial embodied system, under the control of its intrinsic developmental program develops mental capabilities through autonomous real time interactions with its environments by using its own effectors and sensors. Traditionally, a machine is not autonomous when it develops its skills, but a human is autonomous throughout its lifelong mental development.
Current advances in neuroscience illustrate this principle. For instance, if the optic nerves originating from the eyes of an animal are connected into the auditory pathway early in life, the auditory cortex gradually takes on representation that is normally found in the visual cortex. Further, the rewired animals learn successfully to perform vision tasks with the auditory cortex. This discovery advises that the cortex is governed by developmental principles that work for both auditory and visual signals. For instance, the developmental program of the monkey brain dynamically elect sensory input, according to the actual sensory signal that received, and the selection process is active throughout adulthood.
The Development of Multifingered Robot
Elaborate research has been done on the development of multifingered robot hand, which is employed as prosthetic hand or in humanoid robots for the past two decades. Power grasping and precision grasping are two areas in which the former relates to the application of robots carrying heavy loads. Many models and algorithms have been developed for manipulating objects with multifingered robot hand. In the current years, research is focused towards the manipulation in which the robot fingers are made from soft material. Identification of suitable soft material as substitute for the human skin is a tedious and the deformation effect of soft finger and/or object is common issue in the development of such robot hand.
The development of soft fingers is related fundamental area in the soft manipulations. Related to the modeling of a soft hand Xydas. Developed a contact model and studied soft finger tip contact mechanics using FEM and validated the results by experiments. Byoung-Ho Kim analyzed the fundamental deformation effect of soft finger tip in two fingered object manipulation.
Takahiro Inoue focused on formulating elastic force and potential energy equation for the deformation of fingers which are represented as an infinite number of virtual spring s standing vertically. Elaborate research has been done on soft finger tip manipulations but only a few attempts have been made on power grasping. Analytical model for force distribution in power grasps has been developed by Mirza. Developed a method calculating additional grasping force required for stable power grasping of objects.
A simple contact model as applied to power grasping has been developed and force deformation relationship has been formulated. The geometrical relationship between deformation and contact width is first proposed. The total contact which is based on the contract which is based on the contact parameters, material property, and geometrical data and material property is found by using the compressional strain mechanism.
The development of soft fingers is related fundamental area in the soft manipulations. Related to the modeling of a soft hand Xydas. Developed a contact model and studied soft finger tip contact mechanics using FEM and validated the results by experiments. Byoung-Ho Kim analyzed the fundamental deformation effect of soft finger tip in two fingered object manipulation.
Takahiro Inoue focused on formulating elastic force and potential energy equation for the deformation of fingers which are represented as an infinite number of virtual spring s standing vertically. Elaborate research has been done on soft finger tip manipulations but only a few attempts have been made on power grasping. Analytical model for force distribution in power grasps has been developed by Mirza. Developed a method calculating additional grasping force required for stable power grasping of objects.
A simple contact model as applied to power grasping has been developed and force deformation relationship has been formulated. The geometrical relationship between deformation and contact width is first proposed. The total contact which is based on the contract which is based on the contact parameters, material property, and geometrical data and material property is found by using the compressional strain mechanism.
Deployment Subsystem and Attitude Control Subsystem of STARS-I
Deployment subsystem is one of important subsystems for STARS-I mission to verify TSR technology on orbit, and it is mounted on mother satellite. Its main objectives are to give an initial velocity of daughter satellite for deployment, and to deploy and to retrieve daughter satellite by tether control.
Eject unit makes an initial velocity of daughter satellite, here mother satellite has a velocity due to reaction force. Hook attached to motor presses the spring, and hook unlatch the spring, then spring is extended by its potential energy. Thus, bowl supported by the spring gives an initial velocity of daughter satellite.
Deployment unit controls tether deployment and retrieval. It contains of tether reel, motor, and the torque transmission device, which keeps constant torque. Tether can avoid excessive tension and its sudden change. Fundamentally, tether deployment and retrieval is controlled by motor velocity control. When excessive tension is applied on tether, differential rotation of tether reel and motor are occurred due to the permanent wave torque.
Attitude control subsystem is very important to employ attitude control function of Tethered Space Robot (TSR). Attitude of TSR is controlled by tether position and tensions of the arm and mass centre of the robot. Since relation of tether extension position and lines of tether attachment point and mass centre of the robot is operated by arm motion, torque due to tether tension acting on the robot. There fore the two degrees of freedom for arm motion around the tether extension line axis, and TSR attitude can be controlled around two vertical axis of tether extension line.
Two motors are equipped on daughter satellite in attitude control subsystem. Motor 1 is mounted on the main body of daughter satellite, and actuates the bowl. Motor 2 is mounted on the bowl, and actuates the arm. As a result the arm end attached to tether can be places in spatial space, and then attitude control around tether extension line is possible.
Eject unit makes an initial velocity of daughter satellite, here mother satellite has a velocity due to reaction force. Hook attached to motor presses the spring, and hook unlatch the spring, then spring is extended by its potential energy. Thus, bowl supported by the spring gives an initial velocity of daughter satellite.
Deployment unit controls tether deployment and retrieval. It contains of tether reel, motor, and the torque transmission device, which keeps constant torque. Tether can avoid excessive tension and its sudden change. Fundamentally, tether deployment and retrieval is controlled by motor velocity control. When excessive tension is applied on tether, differential rotation of tether reel and motor are occurred due to the permanent wave torque.
Attitude control subsystem is very important to employ attitude control function of Tethered Space Robot (TSR). Attitude of TSR is controlled by tether position and tensions of the arm and mass centre of the robot. Since relation of tether extension position and lines of tether attachment point and mass centre of the robot is operated by arm motion, torque due to tether tension acting on the robot. There fore the two degrees of freedom for arm motion around the tether extension line axis, and TSR attitude can be controlled around two vertical axis of tether extension line.
Two motors are equipped on daughter satellite in attitude control subsystem. Motor 1 is mounted on the main body of daughter satellite, and actuates the bowl. Motor 2 is mounted on the bowl, and actuates the arm. As a result the arm end attached to tether can be places in spatial space, and then attitude control around tether extension line is possible.
Robotic System to Increase Production Efficiency and Capacity
Robotics, automation and control play an important role in manufacturing in different industries. The art of robotics and intelligent control has been transferred into the automated systems development. The most important field in controls and robotics is the working of a system with maximum accuracy and minimum errors and if an error occurs the system should be capable of taking a significant action against it.
In manufacturing lines are usually a number of inter related processes which should coherently work efficiently to result in an efficient production. However if there is bottleneck at any stage the whole production line should run at a lower efficiency and capacity. Improvement may need to be made using lean manufacturing regarding some of the manufacturing aspects but these are small incremental changes and do not play any vital role to enhance the production efficiency and capacity.
This article is describing a industry collaborative project to investigate a manufacturing production line and identify the bottlenecks. The goal was to design and develop a robotic or automated system to overcome the bottleneck process problems in order to increase the manufacturing efficiency to reach the desired production capacity. Base on the investigation carried out by the company involved, available automated systems do not cover the whole production line and the custom made are extremely expensive. Therefore the idea was to come up with a solution which was within a reasonable budget for the company.
An automated transportation and manipulation flexible robotic system for handling, banding, snapping, and sorting of general purpose labels would improve substantially overall production efficiency of the concerned company where a large scale investment in new equipment could not be made. The goal was to almost double the production by automating a serious bottleneck in the manufacturing line. A typical range of different size and shape labels to demonstrate the handling complexity of the required robotic system.
In manufacturing lines are usually a number of inter related processes which should coherently work efficiently to result in an efficient production. However if there is bottleneck at any stage the whole production line should run at a lower efficiency and capacity. Improvement may need to be made using lean manufacturing regarding some of the manufacturing aspects but these are small incremental changes and do not play any vital role to enhance the production efficiency and capacity.
This article is describing a industry collaborative project to investigate a manufacturing production line and identify the bottlenecks. The goal was to design and develop a robotic or automated system to overcome the bottleneck process problems in order to increase the manufacturing efficiency to reach the desired production capacity. Base on the investigation carried out by the company involved, available automated systems do not cover the whole production line and the custom made are extremely expensive. Therefore the idea was to come up with a solution which was within a reasonable budget for the company.
An automated transportation and manipulation flexible robotic system for handling, banding, snapping, and sorting of general purpose labels would improve substantially overall production efficiency of the concerned company where a large scale investment in new equipment could not be made. The goal was to almost double the production by automating a serious bottleneck in the manufacturing line. A typical range of different size and shape labels to demonstrate the handling complexity of the required robotic system.
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