Department of Electrical and Computer Engineering, University of Bridgeport, USA Despite this feature, PLC-based control systems for robot manipulators are quite rare and, in general, limited to simple Cartesian or . Two pneumatic cylinders which act as component pusher. USB Port, Profibus or Ethernet Connection. Pneumatic Industrial Manipulators Involving Cartesian and. Joint Control in actuated modules as part of this hybrid electro-pneumatic proposed system. years later, they developed an autonomous joint connection mechanism for these . The dynamics model establishes the relationships Serrt::e pfocedufca .. j(e).e. () where J(0) is the jacobian matrix of the robot manipulator, 9 = [G],
Due to this industrial revolutiontechnological advances now allow the manufacturer to invent and create new ideas, product in mass production with enhanced quality [ 11 ]. The most of industrial processes uses manipulator arms for picking and placing the objects or products in close proximity of previously placed objects.
The task assigned to the robot arms can be performed repeatedly with high accuracy and with precise movements of joint angles [ 12 ]. The common industrial manipulator is often referred as robot arm with joints and angles as shown in figure 1.
The robot arm used in our application is an articulated arm consists of all revolute joints. The articulated robot arm has maximum flexibility and can reach over and under the objects. As all joints are revolute these robots can cover large workspace and joints are easy to seal. The robot manipulators are assigned to accomplish the specific task in unstructured environment with minimal joint movements and best shortest path Figure 1.
Robot arm with joint angle. The robot motion path planning has been studied more than two decades and there are so many contributions made on this problem [ 13 ].
Deriving the best possible inverse kinematic solution for end effector is challenging and difficult. Some of the challenging aspects in designing reverse kinematic solution are: States Space As the manipulator is design for pick and place application, the manipulator pick up the part and place it in relative positions such as good part position or bad part or rejection area according to the sensory data. So the states finding for the robot manipulator is finite.
The arm has its work space and it can reach to those positions by different paths. Initial State The initial state for the robot manipulator could be any state depends on the signal send by the sensors to the arm. But at the start of the program the manipulator always go to the home or nesting position. Action The manipulator action is depend on the perceived signal of the sensors camera, part detect sensor, etc.
The manipulator takes action after the signal send to the controller by sensors and controller decides the movement of arm. So manipulator moves toward the destination area by avoiding the obstacles in the path as well as within the time limit and with respective speed.
To reach to the goal or object manipulator has to find out the best possible path with minimal joint angle movement within its work space. The end effector will try to reach the object as soon as x and y coordinates are calculated. Transition Model The transition model for the manipulator is depending on the action taken.
At the start the manipulator returns to the homing position. So we will consider the initial state as the homing position, but not all the time.
The camera mounted on the end effector will continuously feed the current position coordinates of the robot manipulator to the controller and the algorithm controls the motion of robot arm. The complete transition model is shown in figure Figure 2.
Transition model of the system. Path Cost The path cost of this application is varies according to the product cost, which company parts you are using for the system assembling, and other factors. The complete flow chart of the application designed and implemented as given in figure Figure 3.
Flow chart of the complete process. To achieve the goal of the application, the position trajectories calculation of robot manipulator is the most difficult task, as it has to avoid the obstacle and reach to the product picking [ 14 ]. As stated in above problem transition state, for this robot manipulator there are lots of possible path to reach object.
Among those paths, the best path will have the minimal joint movements and shortest distance within its workspace. There are lots of algorithms and techniques have been developed for finding the inverse kinematics of the manipulator. The robot manipulator position, path planning and motion control in 3 dimensional workspace become a key factor for control system design engineers and robot manufacturer. The robot arm should be self-proficient, flexible, low power consumptions, fully efficient.
Solution methodology Dealing with complex, higher level control system with continuous interactive subsystem in dynamic environment is difficult and requires sophisticated and intellectual controller with continuously process optimization. We proposed the solution for above stated problem in this section. The proposed solution has been applied and tested on robot manipulator with 5 DOF. The experimental set up is explained in next section.
In this experiment we are using position based algorithm in combination with Image based algorithm to finding the best possible solution for our stated problem.
As we are implementing Artificial Intelligence in the robot arm control system based on PLC, we have to use search algorithms, inference engine etc.
The system is completely knowledge based as uses the sensors, camera and applies the action on the robot arm and actuators. Solving the inverse kinematics becomes complex and nonlinear as the number of degrees of freedom of the manipulator increases. The position based search algorithm uses the visual data provided by the imaged based algorithm and calculates the joint velocity and angles to form the inverse kinematic solution in 3 dimensional workspace [ 16 ].
By adding vision or imaged based algorithm, the robotic control system is more flexible, adaptable and increases the accuracy in the joints movement Figure 4. With its ability to elongate, compress, and bend in multiple directions simultaneously, the octopus arm is the representative of soft manipulators in nature Kier and Stella, Another example is the human hand; the rigid bone phalanges and the soft ligamentous joints contribute to the overall strength while also providing the necessary flexibility of the human fingers Kapandji, With such a manipulator design humans are undoubtedly the most advanced animals, as their manipulator design evolved to allow the crafting of objects and construction of complex structures, from micro-machinery to large buildings.
The early work on robotics focused on the design of arms and manipulators which have been used in industrial applications for several decades Nof, Due to the task definitions, these manipulator designs were required to achieve high precision, large force exertion, and low mechanical flexibility which was compensated with adaptive control strategies Craig et al.
Based on the knowledge and the expertise on rigid body dynamics and inverse kinematics, the initial examples of human inspired robotic hands also utilized rigid body links, fixed degree of freedom DOF joints, and low mechanical flexibility. Changing from a machine-like approach, recently a more bio-inspired method has been suggested to build manipulators which behave like or consists of continuum soft materials.
Soft robotics refers to robots which utilize materials and actuation methods which are soft, flexible, and compliant Laschi and Cianchetti, Many examples of soft robotics take inspiration from biological organisms bio-mimicrywhich have similar properties of those required for soft robots Kim et al.
The development of soft robotics and the integration of soft materials are a significant change in the direction of robotics research.
The integration of soft materials into robotics is driven by both new scientific paradigms and many applications including biomedical, service, and rescue robots Iida and Laschi, The key underlying principle of soft robotics is compliance which allows us to exploit the interaction of the robot with the environment. Using such techniques and methods, soft materials may enable automation of tasks which are currently not possible using existing robotic technologies and solutions Pfeifer et al.
Such systems have the potential to interact more safely within a human unstructured environment and deal with uncertain and dynamic tasks. This could enable the grasping and manipulation of unknown objects in unstructured environments.
Soft robots developed to date demonstrate a variety of design choices, using highly varying actuation and control methods and displaying great creativity in design. Soft robotics has the potential to enable a radical technology change, which encompasses not only a shift in technologies but also approach. These innovative design principles and methodologies many enable a new generation of robots which can become a more integral part of the human environment Albu-Schaffer et al.
Frontiers | Soft Manipulators and Grippers: A Review | Robotics and AI
In this paper, we will review the current state of the art for soft manipulators considering the material and fabrication processes, actuation and sensing methods, and morphology.
The paper concludes with a discussion as to how soft manipulators may be used in the future. The aim of which was to bring together research teams from around the world, to showcase the technologies and approaches for developing softer robots, deviating from the traditional rigid design principles seen in many robots.
The challenge had two elements: The manipulation challenge required dexterous manipulators to be developed which could complete a number of tasks requiring both significant transfer of forces and loads and also highly delicate and fine manipulation; a dichotomy which is often hard to achieve in rigid robotic systems.
The challenge required objects of varying sizes, ranging from smaller delicate ones to awkwardly shaped and heavy objects to be located, grasped and returned to a box. Second, the challenge required an arm to navigate through rigid cylinders and, finally, the manipulator must be capable of opening a door using a door handle.
As such the challenge required the solution developed to show delicate and highly compliant behavior and also supply enough force.
Many robots used a rigid arm combined with a soft manipulator, combining the structural stability of the former with the safe interactions of the latter. Figure 1 shows the manipulator challenge environment and a few of the manipulator solutions which were developed by the teams. The RoboSoft Grand Challenge manipulator challenge, showing the challenge environment and also a number of the manipulator designs created for the challenge. Soft Manipulators In this section, we introduce the main considerations behind the construction of soft manipulators, namely, the materials and fabrication methods used to create such robots, the actuation methods, morphology of manipulators, and finally the soft sensors which can be integrated into manipulators.
Robot Manipulator Control Using PLC with Position Based and Image Based Algorithm
There is much variability in the design of a soft manipulator, as there is a continuous spectrum between soft and rigid manipulators. Finding the optimum point along this scale to achieve the desired functionality, and the associated materials and actuation methods is key to the success of the development of manipulators.
Figure 2 is the overview of the manipulator design space according to the choice of materials used in the design. The four axes displaying precision, structural compliance, DOF, and force exertion do not represent a quantitative results but show design trade-offs and hence suggest design choice for specific tasks or environments. The position of soft and rigid manipulators in the 2D design space.
The axes only show quantitative change. Human hands lie on the diagonal line gray colored of the whole design space which combines soft and hard materials. Two possible pairings of these qualitative measures are possible. The first is precision and DOF: Second, structural compliance and force exertion can be paired: Continuum body manipulators made with soft materials exploit large deformation capacities; therefore, they inherit features such as a higher DOF and structural compliance.
Although the precise control required for real-world applications might be challenging, the compliance offered by soft manipulators overcomes the need for high-computational power and precision. The field of Soft Robotics is very broad, as such, in this review, we aim to cover the key areas of soft robotics manipulation, presenting a representative sample of relevant publications.
Materials and Fabrication Soft robotics exploits the compliance and flexibility of materials to create manipulators which are highly adaptive and allow for safe interactions with objects and the environment.
The choice of material and fabrication techniques used in the construction is therefore key to the development of soft manipulators. By removing the design principles and rules used for rigid robots soft robotics makes room for inspiration and creativity in the design and fabrication methods of such robots.
Soft robotics also makes use of rapid and adaptable fabrication techniques allowing for a rapid design and test cycle, which is often necessary as it can be hard to model and fully predict their behavior. This includes materials such as silicone, rubber, or other elastomeric polymers which can be easily manufactured with varying form factors and material properties Elango and Faudzi, Despite the many advantages of soft materials, their usage does present challenges in terms of the non-linear response, difficulty in modeling, requirement for self-repair, fatigue performance, and potential fabrication limits.
New materials such as foams are being developed for soft robotic applications and have significant potential with innovative properties such as thermally tuneability and self-healing properties Cheng et al. Material Casting and Molding One of the simplest methods for creating soft robotics is using materials casting or molding processes, in which molds, often 3D printed, are used to cast silicone- or elastomer-based structures Marchese et al.
This can lead to the creation of robots using a single casting process which eliminates any problems with bonding or joining materials of different properties Cho et al. Manipulators created using this method include pneumatic operated manipulators Ilievski et al. Other methods of actuation can be used with fabrication, with tendon-driven locomotion robots also created using similar methods Lin et al. This is an extremely rapid method of prototyping and a low cost development method but can lead to manipulators which are planar in structure.
This method can also be used or combined with some of the other processes and techniques used in soft robotics. Shape Deposition Manufacturing SDM is a layered-manufacturing technology which allows the creation of 3D objects by building robots through cycles of depositing material, partial removal of material, further deposition, and the use of sacrificial and support material Merz et al. This hybrid process of molding and machining away unwanted material allows solid, fully 3D parts composed of multiple materials of different properties to be manufactured Cho et al.
Sacrificial support material allows for the construction of complex and intricate geometries and allows for the inclusions of sensors, circuitry or actuators Cham et al.
A key advantage is that complex 3D geometries can be created with limited machinery an allows for internal inclusions of compliant mechanism, sensors and actuators, as demonstrated through robots such as iSprawl Kim et al. Such methods were used to create a gripper with articulated joints Dollar and Howe,and other biomimetic robots, many of which take advantage of the ability to include sensors within the 3D structure Dollar et al. Soft Lithography Photolithography is a process which has been used extensively in many scientific and engineering disciplines including MEMS design, sensor design and optoelectronics.
A similar process, soft lithography, can be used with the same principle, however, using soft materials such as the elastomer poly dimethylsiloxane PDMS or other silicone rubbers. This is a process already widely used for applications such as microfluidics Xia and Whitesides, In this process, patterned or relief surfaces are created using molds of standard photolithography techniques after which layers can be built up Marchese et al.
This allows the inclusion of channels for actuation and the addition of materials such as fiber, paper, or plastic field to provide some inextensibility, which may help facilitate actuation or movement of the robot.
Due to the wide use of soft lithography in microfluidics, the technique and materials are widely understood. Many soft fluidic elastomer robots are produced this way due to the ease with which channels can be created. Silicon elastomer robots using elastic actuation Ilievski et al. Due to layering process used in this method, this process limits the ability to produce truly 3D structures, with robots typically having a planar morphology, unable to achieve an amorphous 3D structure.
Techniques have now been developed to allow 3D printing of soft materials Lipson and Kurman, and also soft actuators, such as dielectric elastomer actuators Rossiter et al. Soft robots can be increasingly fully 3D printed Umedachi et al. It is now possible to entirely 3D print a soft robot, as demonstrated by the inching locomotion robot which uses variable friction legs and SMA actuation Umedachi et al. This uses embedded and omnidirectional 3D printing techniques Wu et al.
However, although 3D printing allows printing flexible materials in fully amorphous forms, these materials used in 3D printing are relatively brittle in comparison to molded rubbers and are therefore often not well suited to some actuation methods which require pressurization of the rubber.
Another 3D printing method which can be used to develop elastomeric soft robots is spray deposition. By spraying uncured silicone onto an existing surface 3D silicone shapes can be formed. Using this method, dielectric elastomer actuators can be developed Araromi et al.
Additionally, this method can be incorporated into a 4D system in which silicone can be deposited to form a multilayered tubular system by forming layers onto of an air-permeable shaft, and this allows the development of inflatable balloon-like structures Coulter and Ianakiev, Modeling and Simulation The dynamics of soft grippers can be difficult to model due to the high number of degrees of freedom present and the non-linear material properties exhibited.
Typical rigid body methods for modeling which assume rigid links between components can not longer be used Verl et al. New techniques to model continuum structures are required. Many methods which analyze soft body structures use constant curvature approximation Camarillo et al. A steady-state model of continuous body system has been developed, although this negates the inclusion of actuators Jones et al.
There are a number of methods for modeling tendon drive continuum robots, and these allow non-constantly curvature of manipulators to be estimated by considering the inherent torsion of the manipulator Renda et al. Methods for modeling tendon-driven manipulators include Jacobian methods Giorelli et al.
By determining the physical constrains of the system and material properties, the behavior of a soft body can be simulated, for many cases, this has been demonstrated to be highly effective Suzumori et al. It is also possible to use FEM methods real time for the control of soft elastomer robots Duriez, There are a limited set of simulators available for modeling the response of soft materials. Some simulators have been developed using non-linear relaxation for kinematic simulation, whereby the system is represented by a system of springs, beams, and masses Lehman and Stanley, ; Cheney et al.
This allows the correct physical simulation of large-scale deformations and dynamics of very soft materials and moves away from traditional non-linear finite element methods. Additionally, soft matter physics engines have also been produced, such as Voxelyze, which can be used with VoxCAD. Using discrete elements, voxels, allows for efficient computation of the force of each constituent element, however, can be less accurate at predicting small scale deformations.
A voxel-based, mass-spring lattices physics engines have also been created, which allow simulation of the dynamics of highly deformable heterogeneous materials Hiller and Lipson, Approaches to develop models which are geometrically exact have also been developed, taking into account non-linearities and distributed weight and payload Trivedi et al.
Actuation Methods Soft robotic manipulators and hands need the ability to bend, stretch, and contract. The elastic and soft properties of the materials used require smart actuators which, unlike electric motors acting between two rigid links of a robotic manipulator, share the property of adaptability and deformability.
Several actuation methods have been studied to this end in soft robotics, by either transmitting the force coming from rigid actuators via cables or pneumatic channels, or by building actuators that can be deformed such as shape memory alloys SMA.
Pneumatic Actuation Bio-inspired artificial muscles driven by pressurized air have been around since the s, where McKibben developed a stretchable tube surrounded by braided chords, which demonstrated the inherent property of contraction when being pressurized, and slacking when under ambient pressure.
McKibben muscles have also been used in segmented continuum robots to provide antagonistic artificial muscles for bending Pritts and Rahn, ; Kang et al. The McKibben technique allows the elastic structure to contract instead of bend and expand; yet, sometimes bending and stretching motion is desirable.
Soft elastic structures without braided chords promote these properties and have been studied and built for manipulation Suzumori et al. Recent advances have shown that unbraided and channeled silicone molds can be used to actuate soft locomotion robots Shepherd et al. The power source for the pneumatic actuation is usually obtained from a compressor but also on-board chemical pressure generation has been explored Onal et al.
Pneumatic actuation has been applied to a variety of bio-inspired robots, such as a robot fish Marchese et al. Many similarities are shared between pneumatic and hydraulic actuators. Both require an internal pressure to operate, either produced by a compressor, a pump or a lightweight device for portability.
The operating principle is essentially the same, and a few pneumatic actuators can be easily converted into hydraulic actuators McCarthy et al.
The weight difference between pneumatic and hydraulic solutions is an important factor for its applications, and it can be explored for the right applications, such as underwater robotics Marchese et al.
It is important to note that this review does not approach traditional pneumatic and hydraulic actuators, as seen in industrial environments and used in heavier robots.
Although we aim to be as comprehensive as possible, such actuator strategies are very well explored and are seldom observed in robots in physical contact with humans. Cable-Driven Actuation To fully minimize the inertia of the manipulator, the actuator force needs to be delivered from the source of actuation over the manipulators limbs to the point of target articulation.
Critically, the method of force transfer must not limit the movement of manipulator or affect its stiffness. Additionally, the actuation system must generate a considerable amount of force at the actuated manipulator point.
Cables can transfer a force from a distant actuator over the manipulator limbs, which enable the moment of inertia to be kept low Camarillo et al.
The cables can have very high tensile strength in their longitudinal axis but are highly flexible and bendable in other directions.
Therefore, they can be guided over complex routes and easily conform to the manipulator structure, carrying forces only in longitudinal axis with no change in size.
There must be some consideration for the inclusion of a rigid source of rotary or linear actuation to control the actuation of the tendons. Many continuum robots make use of cable-driven actuation systems Cieslak and Morecki, ; Gravagne and Walker, ; Hannan and Walker, ; McMahan et al.
Continuum robots often have a continuous and compliant backbone with a large number of degrees of freedom, for which cables form a simple and straightforward solution for attachment and control Walker, Cable-driven actuation has also been applied to replicate an octopus arm with silicone for reaching Calisti et al.
In analogy to the pneumatically actuated fish robot Marchese and Rus,a cable-driven fish robot has been developed y Alvarado and Youcef-Toumi, Tendons are being increasingly adopted for soft robotics, with a large number of manipulator designs choosing to use tendon actuation, including continuum body semi-rigid manipulators Nguyen and Burgner-Kahrs, and octopus inspired robots Calisti et al.
However, the additional requirement for a source of actuation such as a motor or pneumatic actuator can make the systems bulky. Shape Memory Alloys Shape Memory Alloys SMAs have the interesting property of being deformable and capable of returning to the initial shape when heated.