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This paper aims to describe the topic of robot kinematics and provide a modern machine.

The paper examines, in brief, kinematics and robot kinematics, classes, constraints and chains to provide an introduction. An example shows how robot kinematics can benefit the design of advanced machines for industry.

Robot kinematics, in conjunction with mathematics and other disciplines, lead to a greater understanding of robotics design and control.

This paper discusses robot kinematics in brief as a robot design topic in its own right, as well as presenting the Gantry‐Tau robot as a new and interesting kinematic development. As such, the article should be of general interest to robotics engineers and designers.

The aim of this paper is to investigate the effect of wing kinematics change on force generation produced by flapping wings.

Forces produced by flapping wings are measured using a load cell and compared for the investigation. The measured forces are validated by estimation using an unsteady blade element theory.

From the measurement and estimation, the authors found that flapping wings produced positive and negative lifts when the wings are attached with the +30° and −30°, respectively.

The authors quantified the characteristics of change in the force generation by flapping wings for three wing kinematics. The wing kinematics was modified by changing the initial wing attachment angle.

The result may be applicable to design of control mechanism for an insect‐mimicking flapping‐wing micro air vehicle, which has only wings without control surfaces at its tail.

The preliminary work may provide an insight for design strategy of flapping‐wing micro air vehicles with compact and handy configurations, because they may perform controlled flight even without control surfaces at their tails.

The work included here is the first attempt to quantify the force generation characteristics for different wing kinematics. The suggested way of wing kinematics change can provide a concept for control mechanism of a flapping‐wing micro air vehicle.

For efficient trajectory control of industrial robots, a cumbersome computation for inverse kinematics and inverse dynamics is needed, which is usually developed using spatial transformation using Denavit–Hartenberg principle and Lagrangian or Newton–Euler methods, respectively. The model is highly non-linear and needs to deal with uncertainties because of lack of accurate measurement of mechanical parameters, noise and non-inclusion of joint friction, which results in some inaccuracies in predicting accurate torque trajectories. To get a guaranteed closed form solution, the robot designers normally follow Pieper’s recommendation and compromise with the mechanical design. While this may be acceptable for the industrial robots where the aesthetic look is not that important, it is not for humanoid and social robots. To help solve this problem, this study aims to propose an alternative machine learning-based computational approach based on a multi-gated sequence model for finding appropriate mapping between Cartesian space to joint space and motion space to joint torque space.

First, the authors generate sufficient data required for the sequence model, using forward kinematics and forward dynamics by running N number of nested loops, where N is the number of joints of the robot. Subsequently, to develop a learning-based model based on sequence analysis, the authors propose to use long short-term memory (LSTM) and hence, train an LSTM model, the architecture details of which have been discussed in the paper. To make LSTM learning algorithms perform efficiently, the authors need to detect and eliminate redundant features from the data set, which the authors propose to do using an elegant statistical tool called Pearson coefficient.

To validate the proposed model, the authors have performed rigorous experiments using both hardware and simulation robots (Baxter/Anukul robot) available in their laboratory and KUKA simulation robot data set made available from Neural Learning for Robotics Laboratory. Through several characteristic plots, it has been shown that a sequence-based LSTM model of deep learning architecture with non-redundant features could help the robots to learn smooth and accurate trajectories more quickly compared to data sets having redundancy. Such data-driven modeling techniques can change the future course of direction of robotics research for solving the classical problems such as trajectory planning and motion planning for manipulating industrial as well as social humanoid robots.

The present investigation involves development of deep learning-based computation model, statistical analyses to eliminate redundant features, data creation from one hardware robot (Anukul) and one simulation robot model (KUKA), rigorously training and testing separately two computational models (specially configured two LSTM models) – one for learning inverse kinematics and one for learning inverse dynamics problem – and comparison of the inverse dynamics model with the state-of-the-art model. Hence, the authors strongly believe that the present paper is compact and complete to get published in a reputed journal so that dissemination of new ideas can benefit the researchers in the area of robotics.

The purpose of this paper is to estimate aircraft roll angle and rate gyro biases using aircraft kinematics with GPS and low‐quality rate gyros.

The proposed method is motivated by observing the fact that, in typical flight applications with transport, reconnaissance, or surveillance missions, the aircraft flies along relaxed flight paths, and the associated aircraft motion can be considered as the sum of the coordinated flight, low‐frequency motion and non‐coordinated, high‐frequency motion. The proposed scheme utilizes the coordinated flight kinematics to form the relatively simple, low‐order Kalman filter that estimates the aircraft roll attitude and rate gyro biases.

The associated frequency analysis reveals that, for the estimation in the relatively low‐frequency region, the method relies primarily on GPS with the help of coordinated flight kinematics in removing the bias effect from the low‐quality rate gyros. Also, for the estimation in the high‐frequency region the method relies mainly on the numerical integration of the rate gyro for the roll attitude, which enables a high‐bandwidth estimation.

The proposed method is not suitable for flight manoeuvres where a non‐coordinated flight, such as steady heading sideslip, is sustained for a long period of time.

The proposed method has been implemented in a small UAV. The associated flight tests and simulations indicate that the new method has a potential to be used as a backup or a replacement for other complex conventional methods for many flight applications.

This paper has been the first to promote the estimation method that combines aircraft kinematics with GPS and low‐quality rate gyros.

The purpose of this paper is to present the direct kinematic analysis of a heavy‐payload forging manipulator. In the grasping stage, the manipulator is equivalent to a 3‐DOF under‐actuated mechanism. In order to deal with the direct position kinematics of the under‐actuated mechanism, the analysis is performed in two steps.

The paper analyzes the direct position kinematics of the 3‐DOF under‐actuated mechanism as follows: first, the authors add a virtual constraint on the mechanism, convert it to a 2‐DOF fully actuated mechanism and calculate the direct kinematics of the constrained mechanism. Then, the constraint is applied to many different positions and the corresponding direct kinematics of the constrained mechanism are calculated, respectively. Finally, the mechanism with lower gravitational potential energy than any other constrained mechanism is chosen, and its direct position is what is needed for the 3‐DOF underactuated mechanism.

The paper provides a solution for the direct kinematic analysis of a heavy‐payload forging manipulator in the grasping stage. Furthermore, the simulation and experiment results confirm the effectiveness of the solution.

The paper proposes a methodology to deal with the direct position kinematics of the 3‐DOF under‐actuated mechanism in two steps.

The purpose of this paper is to present a novel stretch-retractable single section (SRSS) continuum manipulator which owns three degrees of freedom and higher motion range in three-dimension workspace than regular single continuum manipulator. Moreover, the motion accuracy was analyzed based on the kinematic model. In addition, the experiments were carried out for validation of the theory.

A kinematics model of the SRSS continuum manipulator is presented for analysis on bending, rotating and retracting in its workspace. To discuss the motion accuracy of the SRSS continuum manipulator, the dexterity theory was introduced based on the decomposing of the Jacobian matrix. In addition, the accuracy of motion is estimated based on the inverse kinematics and dexterity theory. To verify the presented theory, the motion of free end was tracked by an electromagnetic positioning system. According to the comparison of experimental value and theoretical analysis, the free end error of SRSS continuum manipulator is less than 6.24 per cent in the region with favorable dexterity.

This paper presents a new stretch-retractable continuum manipulator that the structure was composed of several springs as the backbone. Thus, the SRSS continuum manipulator could own wide motion range depending on its retractable structure. Then, the motion accuracy character of the SRSS continuum manipulator in the different regions of its workspace was obtained both theoretically and experimentally. The results show that the high accuracy region distributes in the vicinity of the outer boundary of the workspace. The motion accuracy gradually decreases with the motion position approaching to the center of its workspace.

The presented SRSS continuum manipulator owns three degrees of freedom. The future work would be focused on the two-section structure which will own six degrees of freedom.

In this study, the SRSS continuum manipulator could be extended to six degrees of freedom continuum robot with two sections that is less one section than regular six degrees of freedom with three single section continuum manipulator.

The value of this study is to propose a SRSS continuum manipulator which owns three degrees of freedom and could stretch and retract to expend workspace, for which the accuracy in different regions of the workspace was analyzed and validated based on the kinematics model and experiments. The results could be feasible to plan the motion space of the SRSS continuum manipulator for keeping in suitable accuracy region.

Pick-and-place tasks are common across many industrial sectors, and many rigid-linked robots have been proposed for this application. This paper aims to alternatively present the development of a continuum robot for low-load medium-speed pick-and-place tasks.

An inversion of a previously proposed dual continuum mechanism, as a key design element, was used to realize the horizontal movements of the CurviPicker’s end effector. A flexible shaft was inserted to realize rotation and translation about a vertical axis. The design concept, kinematics, system descriptions and proof-of-concept experimental characterizations are elaborated.

Experimental characterizations show that the CurviPicker can achieve satisfactory accuracy after motion calibration. The CurviPicker is easy to control due to its simple kinematics, while its structural compliance makes it safe to work with, as well as less sensitive to possible target picking position errors to avoid damaging itself or the to-be-picked objects.

The vertical translation of the CurviPicker is currently realized by moving the flexible shaft. Insertion of the flexible shaft introduces possible disturbances. It is desired to explore other form of variations to use structural deformation to realize the vertical translation.

The proposed CurviPicker realizes the Schöenflies motions via a simple structure. Such a robot can be used to increase robot presence and automation in small businesses for low-load medium-speed pick-and-place tasks.

To the best of the authors’ knowledge, the CurviPicker is the first continuum robot designed and constructed for pick-and-place tasks. The originality stems from the concept, kinematics, development and proof-of-concept experimental characterizations of the CurviPicker.

This paper aims to present a kinematics analysis method and statics based control of the continuum robot with mortise and tenon joints to achieve better control performance of the robot.

The kinematics model is derived by the geometric analysis method under the piecewise constant curvature assumption, and the workspace and dexterity of the proposed robot are analyzed to optimize its structure parameters. Moreover, the statics model is established by the principle of virtual work, which is used to analyze the mapping relationship between the bending deformation and the applied forces/torques. To improve the control accuracy of the robot, a model-based controller is put forward.

Results of the experiments verify the feasibility of the proposed continuum structure and the correctness of the established model and the control method. The force deviation between the theoretical value and the actual value is relatively small, and the mean value of the deviation between the driving forces is only 0.46 N, which verify the established statics model and the controller.

The proposed model and motion controller can realize its accurate bending control with a few deviations, which can be used as the reference for the motion planning and dynamic model of the continuum robot.

This study aims to introduce a multi-configuration, three-finger dexterous hand with integrated high-dimensional sensors and provides an analysis of its design, modeling and kinematics.

A mechanical design scheme of the three-finger dexterous hand with a reconfigurable palm is proposed based on the existing research on dexterous hands. The reconfigurable palm design enables the dexterous hand to achieve four grasping modes to adapt to multiple grasping tasks. To further enhance perception, two six-axis force and torque sensors are integrated into each finger. The forward and inverse kinematics equations of the dexterous hand are derived using the D-H method for kinematics modeling, thus providing a theoretical model for index analysis. The performance is evaluated using three widely applied indicators: workspace, interactivity of fingers and manipulability.

The results of kinematics analysis show that the proposed hand has excellent dexterity. Additionally, three different experiments are conducted based on the proposed hand. The performance of the dexterous hand is also verified by fingertip force, motion accuracy test, grasping and in-hand manipulation experiments based on Feix taxonomy. The results show that the dexterous hand has good grasping ability, reproducing 82% of the natural movement of the human hand in daily grasping activities and achieving in-hand manipulations such as translation and rotation.

A novel three-finger dexterous hand with multi-configuration and integrated high-dimensional sensors is proposed. It performs better than the previously designed dexterous hand in actual experiments and kinematic performance analysis.

An optimal solution method based on 2-norm is proposed in this study to solve the inverse kinematics multiple-solution problem caused by a high redundancy. The current research also presents a motion optimization based on the 2-Norm of high-redundant mobile humanoid robots, in which a kinematic model is designed through the entire modeling.

The current study designs a highly redundant humanoid mobile robot with a differential mobile platform. The high-redundancy mobile humanoid robot consists of three modular parts (differential driving platform with two degrees of freedom (DOF), namely, left and right arms with seven DOF, respectively) and has total of 14 DOFs. Given the high redundancy of humanoid mobile robot, a kinematic model is designed through the entire modeling and an optimal solution extraction method based on 2-norm is proposed to solve the inverse kinematics multiple solutions problem. That is, the 2-norm of the angle difference before and after rotation is used as the shortest stroke index to select the optimal solution. The optimal solution of the inverse kinematics equation in the step is obtained by solving the minimum value of the objective function of a step. Through the step-by-step cycle in the entire tracking process, the kinematic optimization of the highly redundant humanoid robot in the entire tracking process is realized.

Compared with the before and after motion optimizations based on the 2-norm algorithm of the robot, its motion after optimization shows minimal fluctuation, improved smoothness, limited energy consumption and short path during the entire mobile tracking and operating process.

In this paper, the whole kinematics model of the highly redundant humanoid mobile robot is established and its motion is optimized based on 2-norm, which provides a theoretical basis for the follow-up research of the service robot.

In this paper, the whole kinematics model of the highly redundant humanoid mobile robot is established and its motion is optimized based on 2-norm, which provides a theoretical basis for the follow-up research of the service robot.

In this paper, the whole kinematics model of the highly redundant humanoid mobile robot is established and its motion is optimized based on 2-norm, which provides a theoretical basis for the follow-up research of the service robot.

Motion optimization based on the 2-norm of a highly redundant humanoid mobile robot with the entire modeling is performed on the basis of the entire modeling. This motion optimization can make the highly redundant humanoid mobile robot’s motion path considerably short, minimize energy loss and shorten time. These researches provide a theoretical basis for the follow-up research of the service robot, including tracking and operating target, etc. Finally, the motion optimization algorithm is verified by the tracking and operating behaviors of the robot and an example.