Most existing source search algorithms suffer from a high travel cost, and few of them have been analyzed in performance in noisy environments where local basins are presented. In this paper, the theseus gradient search (TGS) is proposed to effectively overcome local basins in search. Analytical performances of TGS and the gradient ascend with correlated random walk (GACRW), which is a variant of correlated random walk, are derived and compared. A gradient field model is proposed as an analytical tool that makes it feasible to analyze the performances. The analytical average searching costs of GACRW and TGS are obtained for the first time for this class of algorithms in the environments with local basins. The costs, expressed as functions of searching space size, local basin size, and local basin number are confirmed by simulation results. The performances of GACRW, TGS, and two chemotaxis algorithms are compared in the gradient field and a scenario of indoor radio source search in a hallway driven by real data of signal strengths. The results illustrate that GACRW and TGS are robust to noisy gradients and are more competitive than the chemotaxis-based algorithms in real applications. Both analytical and simulation results indicate that in the presence of local basins, TGS almost always costs the lowest.

In global localization under the framework of a particle filter, the acquiring of effective observations of the whole particle system will be greatly effected by the uncertainty of a prior-map, such as unspecific structures and noises. In this study, taking the uncertainty of the prior-map into account, a localizability-based action selection mechanism for mobile robots is proposed to accelerate the convergence of global localization. Localizability is defined to evaluate the observations according to the prior-map (probabilistic grid map) and observation (laser range-finder) models based on the Cramér-Rao Bound. The evaluation considers the uncertainty of the prior-map and does not need to extract any specific observation features. Essentially, localizability is the determinant of the inverse covariance matrix for localization. Specifically, at the beginning of every filtering step, the action, which makes the whole particle system to achieve the maximum localizability distinctness, is selected as the actual action. Then there will be the increased opportunities for accelerating the convergence of the particles, especially in the face of the prior-map with uncertainty. Additionally, the computational complexity of the proposed algorithm does not increase significantly, as the localizability is pre-cached off-line. In simulations, the proposed active algorithm is compared with the passive algorithm (i.e. global localization with the random robot actions) in environments with different degrees of uncertainty. In experiments, the effectiveness of the localizability is verified and then the comparative experiments are conducted based on an intelligent wheelchair platform in a real environment. Finally, the experimental results are compared and analyzed among the existing active algorithms. The results demonstrate that the proposed algorithm could accelerate the convergence of global localization and enhance the robustness against the system ambiguities, thereby reducing the failure probability of the convergence.

This paper presents the design of a controller that allows a four-rotor helicopter to track a desired trajectory in 3D space. To this aim, a dynamic model obtained from Euler-Lagrange equations describes the robot. This model is represented by numerical methods, with which the control actions for the operation of the system are obtained. The proposed controller is simple and presents good performance in face of uncertainties in the model of the system to be controlled. Zero-convergence proof is included, and simulation results show a good performance of the control system.

This paper proposes a new technique based on a Parameter-Optimal Iterative Learning Control (POILC) to track a command pitch rate of a high-speed supercavitating vehicle (HSSV). The pitch rate of a supercavitating vehicle has non-minimum phase behavior. Thus, tracking is fundamentally limited to poor performance. To solve this problem, a feed-forward control can be used while using the cavitator as a control input in the feed-forward path to modify the slow response caused by non-minimum phase behavior. The main idea of this paper is to apply the cavitator input with high precision as a feed-forward control to improve tracking performance. The exact value of the feed-forward control is achieved using POILC. However, in the presence of uncertainty, zero convergence of POILC algorithms is threatened. It will be shown that applying adaptive weight in the performance index, the convergence is guaranteed in the presence of uncertainty and also when the system is sign-indefinite. The proposed technique includes an optimal planning to make the error norm monotonically convergent to zero. The convergence and perfect tracking will be guaranteed through a Lyapunov candidate. Performance and significance of the proposed supercavitating vehicle control will be verified by simulation.

The dynamic modeling of a flexible single-link manipulator arm with consideration of backlash in the planetary gear reducer at the joint is presented, and the influence of backlash on the dynamic response of the system is evaluated. A 2K-H planetary gear reducer with backlash was employed as an example to discuss the dynamic modeling of the sub-model of the planetary gear reducer, and the sub-model of the planetary gear reducer was established based on the lumped mass method. The flexible manipulator was regarded as an Euler--Bernoulli beam, and the dynamic model of the flexible manipulator arm with backlash in the planetary gear reducer was determined from Lagrange's equations. Based on the this model, the influence of the backlash in the planetary gear reducer and excitation frequency on the dynamic response of the system were evaluated through simulation, and the results showed that the dynamic response of the system is sensitive to the backlash and the excitation frequency simultaneously, which provides a theoretical foundation for improvement of dynamic modeling and control of the flexible manipulator arm.

Parallel mechanisms possess several advantages such as the possibilities for high acceleration and high accuracy positioning of the end effector. However, most of the proposed parallel manipulators suffer from a limited workspace. In this paper, a novel 6-DOF parallel manipulator with coaxial actuated arms is introduced. Since parallel mechanisms have more workspace limitations compared to that of serial mechanisms, determination of the workspace in parallel manipulators is of the utmost importance. For finding position, angular velocity, and acceleration, in this paper, inverse and forward kinematics of the mechanism are studied and after presenting the workspace limitations, workspace analysis of the hexarot manipulator is performed by using MATLAB software. Next, using the obtained cloud of points from simulation, the overall borders of the workspace are illustrated. Finally, it is shown that this manipulator has the important benefits of combining a large positional workspace in relation to its footprint with a sizable range of platform rotations.

To obtain better performance on unstructured environments, such as in agriculture, forestry, and high-altitude operations, more and more researchers and engineers incline to study classes of biologically inspired robots. Since the natural inchworm can move well in various types of terrain, inchworm-like robots can exhibit excellent mobility. This paper describes a novel inchworm-type robot with simple structure developed for the application for climbing on trees or poles with a certain range of diameters. Modularization is adopted in the robot configuration. The robot is a serial mechanism connected by four joint modules and two grippers located at the front and rear end, respectively. Each joint is driven by servos, and each gripper is controlled by a linear motor. The simplified mechanism model is established, and then is used for its kinematic analysis based on screw theory. The dynamics of the robot are also analyzed by using Lagrange equations. The simulation of the robot gait imitating the locomotion of real inchworm is finally presented.

A new image-based controller is proposed for the robotic system with the joint velocity signals unavailable. The Immersion and Invariance (I&I) observer is applied to estimate the unknown velocity information. Compared with the general velocity observer, the I&I observer can estimate the unknown velocity exponentially. We consider the case that the exact camera parameters are not known. The corresponding adaptive controller is designed for the robot system and the stability is rigorously proven by using Lyapunov theorem. Finally, simulations are performed and the results show the effectiveness of the proposed control approach.

Software engineering plays a key role in state-of-the-art robotics where more effective and efficient software development solutions are needed for implementation and integration of advanced robotics capabilities. Component-based software engineering and model-driven software development are two paradigms suitable to deal with such challenges. This paper presents the analysis, design, and implementation of control software for an Autonomous Underwater Vehicle (AUV). The software development stages are carried out by using a model-driven toolchain that provides support to design and build component-based software for robotics applications. A case study of a high-performance AUV control application and experimental results from a software schedulability analysis are presented.

Three-dimensional (3D) data processing has applications in solving complex tasks such as object recognition, environment modeling, and robotic mapping and localization. Because using raw 3D data without preprocessing is very time-consuming, extraction of geometric features that describe the environment concisely is essential. In this sense, a plane can be a suitable geometric feature due to its simplicity of extraction and the abundance in indoor environments. This paper presents an online incremental plane extraction method using line segments for indoor environments. Our data collection system is based on a “nodding” laser scanner, so we exploit the incremental nature of its data acquisition in which physical rotation and 3D data processing are conducted in parallel. Line segments defined by two end points become supporting elements that comprise a plane, so a large proportion of scan points can be ignored once the line segments are extracted from each scan slice. This elimination of points reduces the algorithm complexity and computation time. Experiments with the tens of complete scan data sets which were acquired from a typical indoor environment demonstrated that our method was at least three times faster than the state-of-the-art methods.

Laparoscopic and Single Port Access Surgery (SPAS) present unique dexterity challenges related to dual-arm operations in confined spaces and tele-manipulation of highly dexterous surgical slaves. In an effort to reduce tele-manipulation burden, new paradigms for semi-automating surgical tasks are needed. This paper presents a new minimal constraint suturing and automated choice of handedness for anthropomorphic dual-arm robots. The automated choice of handedness supports surgeons during tele-manipulation of complex robotic slaves where dexterity and workspace constraints are difficult to learn. This criterion is also used to support automated dual-arm rendezvous for quicker suture exchange during dual-arm suturing. The minimal constraint algorithm presented in this paper allows surgeons to operate within a shared-control tele-manipulation framework whereby the surgeon controls the needle insertion speed and the robot controls the needle orientation while respecting a minimalistic set of tissue constraints. This framework is evaluated on a novel insertable robotic end-effectors platform for SPAS. A simulation study demonstrates the effectiveness of the automated choice of handedness criterion through a study of dexterity limitations of each arm. Additional simulations show the proposed algorithm for automated rendezvous and suture exchange.