A method is presented for the type synthesis of a class of parallel mechanisms having one-dimensional (1D) rotation based on the theory of Generalized Function sets (GF sets for short), which contain two classes. The type synthesis of parallel mechanisms having the first class GF sets and 1D rotation is investigated. The Law of one-dimensional rotation is given, which lays the theoretical foundation for the intersection operations of GF sets. Then the kinematic limbs with specific characteristics are designed according to the 2D and 3D axis movement theorems. Finally, several synthesized parallel mechanisms have been sketched to show the effectiveness of the proposed methodology.

In this paper, the realization of biped walking on even floor, sloping surfaces, and stairs is studied. The motion trajectories for the biped's body and its two feet are modeled by piecewise cubic polynomials. The main features of the biped robot include two variable-length legs and a moving weight which can be positioned side-to-side for balance. The contribution of this paper is gait synthesis and is experimental verification.

In order to provide a novel approach for the operational problems of walking robots, this paper presents a method by which a hexapod robot uses its legs to manipulate an object, and this involves the following two steps. First, two adjacent legs are used to manipulate the object. Next, the supporting legs are required to assist the arms to obtain high manipulability. The manipulation constraints, workplaces, and kinematic models are analyzed using screw theories. Moreover, an optimization algorithm is proposed to reduce energy consumption under stability constraints. We also introduce a manipulation control model that simultaneously considers the supporting and operating legs. Finally, the validity of these methods is proved by the results of experiments and simulations.

This study deals with the problem of trajectory tracking of wheeled mobile robots (WMR's) under non-holonomic constraints and in the presence of model uncertainties. To solve this problem, the kinematic and dynamic models of a WMR are first derived by applying the recursive Gibbs–Appell method. Then, new kinematics- and dynamics-based multivariable controllers are analytically developed by using the predictive control approach. The control laws are optimally derived by minimizing a pointwise quadratic cost function for the predicted tracking errors of the WMR. The main feature of the obtained closed-form control laws is that online optimization is not needed for their implementation. The prediction time, as a free parameter in the control laws, makes it possible to achieve a compromise between tracking accuracy and implementable control inputs. Finally, the performance of the proposed controller is compared with that of a sliding mode controller, reported in the literature, through simulations of some trajectory tracking maneuvers.

The paper presents research on the APF approach for solving the GNRON and local minima problems. The repulsive potential function is modified in order to solve the GNRON problem. A simulated annealing algorithm integrated into the APF has solved the local minimum problem. The improved APF is applied to the path-planning problem of soccer robots. The simulated experiments show the validity of this approach.

This paper proposes a method for task based design of modular serial robotic arms using evolutionary algorithms (EA). We introduce a 3D kinematics and a global optimization for both topology and configuration from task specifications. The search features revolute as well as prismatic joints and any number of DOF to build up a solution without using any design knowledge. A study of the evolution dynamics gives some keys to set evolution parameters that enable artificial evolution. An adapted algorithm dealing with the topology/configuration search tradeoff is proposed, descibed, and discussed. Illustrations of the algorithms results are given and conclusions are drawn from their analysis. Perspectives of this work are given, extending its reach to control and complex system design.

One of the important issues of walking machine active force control is a successful distribution of the body force to the feet to prevent leg slippage. In this paper, a new force distribution method, the Friction Constraint Method (FriCoM), is introduced. The force distribution during the walking of a typical quadruped crawl gait is analyzed by using the FriCoM. Computation results show that the distributed forces of the feet are continuous during the walking. This reflects the change of the force distribution during actual conditions. The comparison with a pseudo-inverse method shows that the FriCoM is more practical. The FriCom also requires less computation time than that by an incremental optimization method. Some problems, such as the singularity in the application of the FriCoM, are discussed. The FriCoM will be used in the active force control of a quadruped robot that is taken as a platform for the research on the study of terrain adaptation.

The paper presents a meta-study of the kinematic, dynamic and electrical parameters for the PUMA 560 robot. Parameter values which have been reported in the literature are transformed into a single system of units and coordinates, and differences in the data and measurement techniques are discussed. New data have been gathered and are presented where the record was incomplete.

Fall-related accidents are among the most serious concerns in elderly people, amputees and subjects with neurological disorders. The aim of this paper was to investigate the behaviour of healthy subjects wearing a novel light-weight pelvis exoskeleton controlled in zero-torque mode while carrying out unperturbed locomotion and managing unexpected perturbations. Results showed that the proposed exoskeleton was unobtrusive and had a minimum loading effect on the human biomechanics during unperturbed locomotion. Conversely, it affected the movement of the trailing leg while subjects managed unexpected slipping-like perturbations. These findings support further investigations on the potential use of powered exoskeletons to assist locomotion and, possibly prevent incipient falls.

The increased use of unmanned aerial vehicles (UAVs) is coincidentally accompanied by a notable lack of sensors suitable for enabling further improvement in levels of autonomy and, consequently, integration into the National Airspace System (NAS). The majority of available sensors suitable for UAV integration into the NAS are based on infrared detectors, focal plane arrays, optical and ultrasonic rangefinders, etc. These sensors are generally not able to detect or identify other UAV-sized targets and, when detection is possible, considerable computational power is typically required for successful identification. Furthermore, the performance of visual-range optical sensor systems may suffer when operating under conditions that are typically encountered during search and rescue, surveillance, combat, and most other common UAV applications. However, the addition of a miniature RADAR sensor can, in consort with other sensors, provide comprehensive target detection and identification capabilities for UAVs. This trend is observed in manned aviation where RADAR sensors are the primary on-board detection and identification sensors. In this paper, a miniature, lightweight X-band RADAR sensor for use on a miniature (710-mm rotor diameter) rotorcraft is described. We present an analysis of the performance of the RADAR sensor in a realistic scenario with two UAVs. Additionally, an analysis of UAV navigation and collision avoidance behaviors is performed to determine the effect of integrating RADAR sensors into UAVs. Further study is also performed to demonstrate the scalability of the RADAR for use with larger UAV classes.

Realisations and concepts are presented on the control of the MANUS wheelchair-mounted telemanipulator arm by severely disabled persons with few residual functions. Functional aspects are stressed as a basis for technical implementations, with special attention to the ergonomics of interactive control of the manipulator-wheelchair system in unstructured human environments. Adaptability of the control is accentuated, both with respect to abilities and impairments of the individual user and with respect to characteristics of the environment and the task to be executed. Some methods to improve adaptability are discussed, and the need for standard interfacing methods is underlined. Control configurations in actual daily use by persons with different severe disabilities are presented in some detail. A first implementation of integrated chin joystick control of MANUS manipulator and electric wheelchair, in daily use by a person with a C4/C5 spinal cord lesion, is reported as an example.

This paper compares three numerical methods for obtaining the joint trajectory of a robot manipulator, which causes movement along the desired Cartesian path. The first solves the kinematic equations, which are given in the Jacobian form, while the other two solve the nonlinear kinematic equations directly by using an iterative computational procedure based on the conjugate gradient technique. The computational efficiency of the proposed methods is estimated in terms of the execution time on a VAX 11/750 minicomputer. It is shown that by using the capacity of microcomputers, these methods could be well used in real-time computation.

This paper presents the design of a new low-cost, easy operation hand having three 1-dof anthropomorphic fingers of a human size. Experimental results on human cylindrical grasping have been used for designing a 1-dof anthropomorphic finger of a human size. The mechanical design of this finger has been mainly focused on a suitable articulated mechanism. This mechanism transmits the power to the phalanxes for a human-like grasping motion and it can be embedded in the body of the finger itself. The design of a three finger hand has been presented as based on the designed finger module. Experimental tests on a built hand prototype have been carried out in order to show the feasibility of the proposed design and validate its operation.

This paper provides a solution to the composite adaptive output feedback tracking control problem for robotic manipulators. The proposed controller utilizes an update law that is a composite of a gradient update law driven by the link position tracking error and a least squares update law driven by the prediction error. In order to remove the controller's dependence on link velocity measurements, a linear filter and a new prediction error formulation are designed. The controller provides semi-global asymptotic link position tracking performance. Experimental results illustrate that the proposed controller provides improved link position tracking error transient performance and faster parameter estimate convergence in comparsion to the same controller using a gradient update law.

Surgical robotics is the study and application of advanced robotic technology to diverse surgical procedures, particularly to minimally invasive surgery. The advanced robotic technology in minimally invasive surgery leads to momentous change in and generates a tremendous impact on surgery, resulting in less pain and scarring, reduced blood loss and transfusions, lower risk of complication, shorter hospital stays and faster recovery periods.

Biped robots have gained much attention for decades. A variety of researches have been conducted to make them able to assist or even substitute for humans in performing special tasks. In addition, studying biped robots is important in order to understand human locomotion and to develop and improve control strategies for prosthetic and orthotic limbs. This paper discusses the main challenges encountered in the design of biped robots, such as modeling, stability and their walking patterns. The subject is difficult to deal with because the biped mechanism intervenes with mechanics, control, electronics and artificial intelligence. In this paper, we collect and introduce a systematic discussion of modeling, walking pattern generators and stability for a biped robot.

This work presents a novel trajectory tracking, hovering, and yaw motion control for quadrotors subject to unknown modeling uncertainties and disturbances. Nonlinear equations of motion are used to model the quadrotor's motion without any simplifying assumptions. An integral backstepping control is developed by defining the tracking errors, their integral, and their first through third time derivatives as the system states. The resulting surge force and roll and pitch moments are shown to asymptotically stabilize the error states subject to bounded disturbances and modeling uncertainties. Similarly, a yaw moment is derived through integral backstepping that simultaneously stabilizes yaw motion errors. The controller performance in simultaneous trajectory and yaw motion tracking is verified through both simulations and experiments.

In this paper, we present a novel structure of a snake-like robot. This structure enables passive locomotion in snake-like robots. Dynamic equations are obtained for motion in a horizontal plane, using Gibbs–Appell method. Kinematic model of the robot include numerous nonholonomic constraints, which can be omitted at the beginning by choosing proper coordinates to describe the model in Gibbs–Appell framework. In such a case, dynamic equations will be significantly simplified, resulting in considerable reduction of simulation time. Simulation results show that, by proper selection of initial conditions, joint angles operate in a limit cycle and robot can locomote steadily on a passive trajectory. It can be seen that the passive trajectory is approximately a Serpenoid curve.

In the present paper, a model of an underactuated robotic hand with tendon driven fingers is proposed. The aim of the project was to study the feasibility of building a mechanical hand with four or five fingers, the movement of which is achieved using a single linear actuator. The mechanism was first modelled in order to study the possible improvement in the ability of a “robotic hand” powered with a single actuator in regard to grasping objects with complex shapes and also in achieving a strong grip on objects. Next, a model of the finger was studied in order to optimize of its parameters. Finally, a five-fingered robotic hand was modelled for potential application as a human hand prosthesis. Our studies on the dynamic and kinematic behaviour of a single finger mechanism permitted us to make the first prototypes of the mechanism. In addition to modelling studies, we also present a prototype of the modelled robotic hand that was developed in order to optimize functionality and simplicity of construction.

In this paper, we propose a bioinspired path planning algorithm for finding a high-quality initial solution based on the pipeline of the Rapidly exploring Random Tree (RRT) method by modifying the sampling process. The modification mainly includes controlling the sampling space and using the probabilistic sampling with the two-dimensional Gaussian mixture model. Inspired by the tropism of plants, we use a Gaussian mixture model to imitate the tree’s growth in nature. In a 2D environment, we can get an approximate moving point’s probabilistic distribution, and the initial path can be found much quickly guided by the probabilistic heuristic. At the same time, only a small number of nodes are generated, which can reduce the memory usage. As a meta-algorithm, it can be applicable to other RRT methods and the performance of underlying algorithm is improved dramatically. We also prove that the probabilistic completeness and the asymptotic optimality depend on the original algorithm (other RRTs). We demonstrate the application of our algorithm in different simulated 2D environments. On these scenarios, our algorithm outperforms the RRT and the RRT* methods on finding the initial solution. When embedded into post-processing algorithms like the Informed RRT*, it also promotes the convergence speed and saves the memory usage.