Repetitive motion planning (RMP) is important in operating redundant robotic manipulators. In this paper, a new RMP scheme that is based on the pseudoinverse formulation is proposed for redundant robotic manipulators. Such a scheme is derived from the discretization of an existing RMP scheme by utilizing the difference formula. Then, theoretical analysis and results are presented to show the characteristic of the proposed RMP scheme. That is, this scheme possesses the characteristic of cube pattern in the end-effector planning precision. The proposed RMP scheme is further extended and studied for redundant robotic manipulators under joint constraint. Based on a four-link robotic manipulator, simulation results substantiate the effectiveness and superiority of the proposed RMP scheme and its extended one.

A magnetically controlled spiral capsule robot is designed. When the robot is running in a pipe filled with mucus, computational fluid dynamics is used to analyze the fluid field (velocity, streamlines, and vorticity) in the pipe, and particle image velocimetry is used to measure the above fluid field surrounding the robot. The measured fluid field is basically similar to the numerical result. The relationship between the operating parameters of the robot and the performance of the robot is further calculated and analyzed. The results show that the resistance to the robot in the forward direction, average turbulent intensity of the fluid surrounding the robot, and maximum fluid pressure to the pipe wall are proportional to the robotic translational speed. The resisting moment of the robot in the forward direction, average turbulent intensity of the fluid surrounding the robot, and maximum fluid pressure to the pipe wall are proportional to the robotic rotational speed.

This paper proposes a new type of hybrid manipulator that can be of extensive use in industries where translational motion is required while maintaining an arbitrary end-effector orientation. It consists of two serially connected parallel mechanisms, each having three degrees of freedom, of which the upper platform performs a pure translational motion with respect to the mid-platform. Closed-form forward and inverse kinematic analysis of the proposed manipulator has been carried out. It is followed by the determination of all of its singular configurations. The theoretical results have been verified numerically, and the 3D modeling and simulation of the manipulator have also been performed. A simple optimal design is presented based on optimizing the kinematic manipulability, which further demonstrates the potential of the proposed hybrid manipulator.

In this study, several joint axis orientations on equilateral platforms and the limbs of 3-UPU parallel manipulators (PMs) are examined. The generated joint layouts for the platforms were matched with each other to generate and enumerate manipulator architectures based on certain assumptions. The structures of thus obtained manipulators are examined and limb types were determined. These limb types were analyzed using screw theory. The instantaneous mobility of the manipulators and the motion characteristics of the moving platforms are tabulated. The finite mobility analysis of one of the manipulators is performed using a software package as an example. Among several different 3-UPU PM architectures, 118 novel 3-UPU PMs with non-parasitic 3-degrees-of-freedom are significantly important. The classified 3-UPU PMs with determined motion characteristics can be used by researchers as a design alternative for their specific design task.

We present a data fusion control scheme for the hand-held camera of the SCORBOT-ER VII robot arm for learning visual tracking and interception. The control scheme consists of two modules: The first one generates candidate actions to drive the end-effector as accurate as possible directly above a moving target, so that the second module can handily take over to intercept it. The desired camera-joint coordinate mappings are generalized by Elman neural networks for a tracking module. The intercept module then determines a suitable intercept trajectory for the robot within the required conditions. The simulation results support the claim that it could be successfully applied to track and intercept a moving target.

A Jacobian-based algorithm that is useful for planning the motion of a floating rigid body operated using two input torques is addressed in this paper. The rigid body undergoes a four-rotation fully reversed (FR) sequence of rotations which consists of two initial rotations about the axes of a coordinate frame attached to the body and two subsequent rotations that undo the preceding rotations. Although a Jacobian-based algorithm has been useful in exploring the inverse kinematics of conventional robot manipulators, it is not apparent how a correct FR sequence for a desired orientation could be found because the Jacobian of FR sequences is singular as well as being a null matrix at the identity. To discover the FR sequences that can synthesize the desired orientation circumventing these difficulties, the Jacobian algorithm is reformulated and implemented from arbitrary orientations where the Jacobian is not singular. Due to the insufficient degrees-of-freedom of four-rotation FR sequences required to achieve all possible orientations, the rigid body cannot achieve certain orientations in the configuration space. To best approximate these infeasible orientations, the Jacobian-based algorithm is implemented in the sense of least squares. As some orientations can never be attained by a single four-rotation FR sequence, two different four-rotation FR sequences are exploited alternately to ensure the convergence of the proposed algorithm. Assuming the orientation is supposed to be manipulated using three input torques, the switching Jacobian algorithm proposed in this paper has significant practical importance in planning paths for aerospace and underwater vehicles which are maneuvered using only two input torques due to the failure of one of the torque-generation mechanisms.

Selective compliance articulated robot arms (SCARA) robotic manipulators find wide use in industry. A nonlinear optimal control approach is proposed for the dynamic model of the 4-degrees of freedom (DOF) SCARA robotic manipulator. The dynamic model of the SCARA robot undergoes approximate linearization around a temporary operating point that is recomputed at each time-step of the control method. The linearization relies on Taylor series expansion and on the associated Jacobian matrices. For the linearized state-space model of the system, a stabilizing optimal (H-infinity) feedback controller is designed. To compute the controller’s feedback gains, an algebraic Riccati equation is repetitively solved at each iteration of the control algorithm. The stability properties of the control method are proven through Lyapunov analysis. The proposed control method is advantageous because: (i) unlike the popular computed torque method for robotic manipulators, it is characterized by optimality and is also applicable when the number of control inputs is not equal to the robot’s number of DOFs and (ii) it achieves fast and accurate tracking of reference setpoints under minimal energy consumption by the robot’s actuators. The nonlinear optimal controller for the 4-DOF SCARA robot is finally compared against a flatness-based controller implemented in successive loops.

This paper considers the magnitude of the gripping power, i.e., the internal force that depends on the grasping posture or object orientation in a two-dimensional grasp by two contact points with friction. Expressing the effect of variations in the object posture as the direction of an external force, we propose an “internal force diagram.” The internal force necessary to create a statically stable grasp is depicted in the object coordinate frame. Then, a polar coordinate system is introduced in which the orientation represents the direction of the external force, while the distance from the origin represents the minimum necessary internal force. We demonstrate a method based on friction cone configurations to manually draw the internal force diagram, using only a ruler and a compass. The validity of this drawing method is confirmed by a comparison with computer-generated plots. Finally, the characteristics of the internal force diagram are discussed.

This paper introduces an event-based decentralized control scheme for the cooperation between multiple manipulators. This is in contrast to the common practice of using only centralized controls for such cooperation which, consequently, greatly limit the flexibility of robotic systems. The manipulators used in the present system are very simple with only two degrees of freedom, while even one of them is passive. Moreover these manipulators use very few and commonly available sensors only. Computer simulations indicated the applicability of the event-based decentralized control scheme for multi-manipulator cooperation, while real-life experimental implementation has proved that the proposed decentralized control scheme is fairly applicable for very simple and even under-actuated systems too. Hence, this work has opened new doors towards further research in this area. The proposed control scheme is expected to be equally applicable for any mobile or immobile multi-robotic system.

This paper investigates the kinematics and the optimization of a generic robotic structure composed by N serial rotary joints and actuated with a mono-directional tendon system. In the first part of the paper, the specific case that brought us to develop this study is introduced; the main motivations and the scenario with its specific constraints and design choices have been described.

Since a complete and detailed analysis of an n-R serial structure with this kind of characteristics could not be found in the literature, the study of the kinematics and the parameter optimization of such a structure is treated as generally as possible, in order to make the procedure and the results applicable for any similar structure. Finally, in the last part, through the introduction of specific constraints and the definition of the parameters, the general analysis has been applied to the specific case of study: the preliminary study of a finger exoskeleton for an astronaut suit.

The positioning of a wheeled robot is an imperative manipulation problem in mobile robotics. Odometry is a familiar method for determining the relative position of a mobile robot. It comprises the detection of a set of kinematic parameters that permit reconstructing the robot's absolute position and orientation starting from the wheels' encoder measurements. This paper deals with the determination of better relative localization of a mobile robot by means of odometry by considering the influence of parameters namely total weight, speed, diameter of wheel, and width of wheel. Experiments have been conducted based on L9 orthogonal array suggested in Taguchi method to obtain the optimum condition. A mathematical model has also been developed for the mobile robot with the help of MINITAB software.

This paper investigates artificial neural network (ANN)-based simulators as an alternative to physics-based approaches for evolving controllers in simulation for a complex snake-like robot. Prior research has been limited to robots or controllers that are relatively simple. Benchmarks are performed in order to identify effective simulator topologies. Additionally, various controller evolution strategies are proposed, investigated and compared. Using ANN-based simulators for controller fitness estimation during controller evolution is demonstrated to be a viable approach for the high-dimensional problem specified in this work.

This paper deals with a generic modeling and vision-based control approach for a broad class of parallel mechanisms. First, a generic architecture representing several families is proposed. Second, inspired by the geometry of lines, a generic differential inverse kinematic model according to the proposed generic structure is introduced. Finally, based on the image projection of cylindrical legs, a kinematic vision-based control using legs observation is presented. The approach is illustrated and validated on the Gough–Stewart and Par4 parallel robots.

In this paper, the joint angles of a two link planar manipulator are calculated by using inverse kinematics equations together with some geometric equalities. For a given position of the end-effector the joint angle and angular velocity of the links are derived. The analyses contains many equations which have to be solved. However, the solutions are rather cumbersome and complicated, therefore a program is written in Fortran 90 in order to do, the whole calculation and data collection. The results are given at the end of this paper.

This paper deals with the controllability of biologically inspired snake-like mechanisms. Motion equations of the generic snake-like mechanism and investigations on its controllability lead to extremely complicated mathematical representations. The authors establish a physical analogy between the undulatory snake locomotion and object grasping. Based on this analogy, they propose a controllability criterion concerning the motion of the mobile mechanism. Results of dynamic simulations of the controlled system systematically point to the validity of the analogy-based controllability criterion. The purpose of this work is to achieve an understanding of the undulatory motion which constitutes the basis of a biologically motivated experimental setup.

This paper demonstrates a new method in sampling environmental variables and underwater currents using special devices with a particular technique. The project involves developing a set of robots as the tools for data collection, and developing a system that can interpret the data collected. The ‘ocean' currents can be mapped using a flock of robots by dropping them into the ocean. As they descend, they record the desired sensory information such as salinity, temperature, pressure, the presence of specific chemicals, etc., along with other variables required for the system to function. Once at a predefined depth the robots start ascending and still continue collecting data until they reach the surface. Back on the surface, they communicate the collected data to a base computer in a ship or on land, through satellite or other means. The base computer collects the data from every recovered member of the flock and reconstructs the path they took underwater. Then using this path, it estimates the vectors of the oceanic currents. The environmental variables can be displayed in 3D for the sampled area.

We have developed an underwater robotic fish using a unique three-layer electrostatic film motor. In the robotic fish, the unique motor actuates a flexible caudal fin to propel the robot via an elaborate power transmission system. In the present study, we describe the major disadvantages of the previous prototype of the robotic fish and improvements of the prototype. In addition, we present experimental evaluations related to the control parameters and locomotion performance of the robotic fish. These control parameters include the frequency and initial phase of AC voltage, and the amplitude and period of frequency sweeping. A simple theoretical model concerning the power transmission system of the robotic fish is also analyzed to provide a possible explanation for the unique swimming control. By appropriately adjusting these control parameters, we achieve cruising, emerging, submerging, and turning of the robotic fish even though only the caudal fin is active. Finally, we show smooth human-operated turn-around motion similar to that seen in real fish. Based on these experimental results, we further clarify the relationships between the open-loop motor pattern and motion parameters.

One of the important characteristics of an autonomous robot lies in the capability of self-organizing its own behaviors in order to adapt to an unknown environment. The goal of this paper is to present an effective means for investigating such a capability, which enables us to graphically build a model of the autonomous robot and dynamically observe the emergence of reactive behaviors as a result of external stimulus controlled behavioral self-organization. In particular, the paper describes an integrated software workbench, called C4 (which stands for Create, Coordinate, Condition, and Co-evolve), for modeling and simulating autonomous robotic systems, e.g., legged and dual-arm ones. The module create enables us to build top-down graphical models of novel mechanisms, followed by primitive motion pattern (e.g., gaits) specification and visualization in the coordinate module. Learning mechanisms, as embedded in module condition further allow us to test how the animated robots acquire new behavioral rules triggerable by external stimuli. Finally, the module co-evolve facilitates the analysis of the distributed intelligence of robot groups, which manifests itself from the behaviors emergent from the interaction among individual robots.

This work presents an analysis of the mechanics of biped running with a heuristic control strategy for stable running. A tractable model of the mechanics is presented through principles, measures, and a time-distributed perspective. This model motivates the control strategy and provides a basis for extending the strategy to more general systems. The control strategy consists of a simple set of four rules, where the key rule considers the leg length upon liftoff. The Steady-State Index is proposed as a characterization of biped running. It identifies and relates the parameters affecting running and has broad applicability to both biological and robotic systems.