The objective of this work is to construct a robot that is based on 3D printing to meet the low-cost and light structures. The Computer-aided-design model is used with LabVIEW to simulate the given trajectory. Users of the simulation of such methodology can preview the simulated motion and perceive and resolve discrepancies between the planned and simulated paths prior to execution of a task. The advantages of this study are the lack of need to mount extra sensors on realistic robot to measure joint space coordinates, simplifying the hardware. These outcomes can also be used in an undergraduate robotics course.

The various vision-based tactile sensors have been developed for robotic perception in recent years. In this paper, the novel soft robotic finger embedded with the visual sensor is proposed for perception. It consists of a colored soft inner chamber, an outer structure, and an endoscope camera. The bending perception algorithm based on image preprocessing and deep learning is proposed. The boundary of color regions and the position of marker dots are extracted from the inner chamber image and label image, respectively. Then the convolutional neural network with multi-task learning is trained to obtain bending states of the finger. Finally, the experiments are implemented to verify the effectiveness of the proposed method.

This paper presents a Chebyshev Pseudospectral (PS) method for solving the motion planning problem of nonholonomic mobile robots with kinematic and dynamic constraints. The state and control variables are expanded in the Chebyshev polynomial of order N, and Chebyshev–Gauss–Lobatto (CGL) nodes are provided for approximating the system dynamics, boundary conditions, and performance index. For the lack of enough nodes nearby the obstacles, the interpolation of trajectory may violate the obstacles and the multiple-interval strategy is proposed to deal with the violation. Numerical examples demonstrate that multiple-interval strategy yields more accurate results than the single-interval Chebyshev PS method.

In this paper we designed an optimal trajectory generation (OTG) method to generate easy and errorless continuous path motion with quick converging using Grey Wolf Optimization (GWO) method. The proposed OTG method finds the trajectory path with minimum tracking error, combined speed, joint increasing speed wrinkle, as well as joint lurching move to follow an error-free smooth continuous path.

Aiming at planning the welding path of complex ship components, a welding path planning optimization model was constructed with the shortest welding path and using the target and the welding process and welding starting and ending points as constraints. Based on the model, an improved ant colony algorithm with dynamic adaptive parameters was proposed to complete the path planning work. Simulation results showed that, compared with other classical optimization algorithms, the proposed algorithm improved optimization speed while ensuring optimization effect and achieving better results in path planning of complex ship components.

In this paper, a sliding mode control using a control point concept is proposed for an under-actuated quadrotor. The proposed controller controls the position of the control point, a displaced point from the quadrotor’s geometric center, and the yaw angle. This method solves singularity issues in control matrix inversion and enables the utilization of the multi-input multi-output equation to derive the control inputs. The sliding surface is designed to control four outputs while stabilizing roll and pitch angles. Simulation and experimental results show the effectiveness and robustness of the proposed controller in the tracking of a trajectory under parametric uncertainties.

This paper addresses the tracking problem for uncertain nonlinear sandwich systems that consist of two nonlinear subsystems and saturation nonlinearity, which is sandwiched between the subsystems. The considered sandwich system is also subject to a nonsymmetric input saturation constraint. Due to the nonsmooth characteristics of sandwiched saturation nonlinearity and also the input saturation function, the design procedure deals with hard challenges. To overcome these difficulties, a recursive approach is suggested that consists of two phases. For the implementation of the proposed approach, a tracking problem is solved in each phase. In the first phase, the second subsystem with sandwiched saturation nonlinearity is considered and the output tracking problem of the desired time-varying reference signal is solved using backstepping method. The outcome of the first phase is the desired reference signal that should be tracked by the first subsystem in the next phase. In the second phase, the robust control input is designed for the first subsystem by employing adaptive sliding mode technique such that, despite the nonsymmetric input saturation constraint, model uncertainty and external disturbances, the output of the first subsystem follows the desired signal that is obtained in the previous phase. The simulation results for a mechanical sandwich system are illustrated to verify the effectiveness of the proposed control method.

In brachytherapy, the manual implantation of seeds is not accurate leading to side effects and limiting the use of new procedures. Robotics solutions have to be fully suitable for medical applications especially considering the operating room. This paper investigates a delta robot solution for improving the accuracy of the prostate brachytherapy procedure by proposing a compact and lightweight robot. In addition, the design was thought as a comanipulated robot for a better acceptability and human–machine interaction. The robot kinematics and singularities were determined and the theoretical capability in term of resolution and force feedback was evaluated. A prototype was built in order to experimentally measure the capability of this first prototype.

Efficient algorithm integration is a key issue in aerial robotics. However, only a few integration solutions rely on a cognitive approach. Cognitive approaches break down complex problems into independent units that may deal with progressively lower-level data interfaces, all the way down to sensors and actuators. A cognitive architecture defines information flow among units to produce emergent intelligent behavior. Despite the improvements in autonomous decision-making, several key issues remain open. One of these issues is the selection, coordination, and decision-making related to the several specialized tasks required for fulfilling mission objectives. This work addresses decision-making for the cognitive unmanned-aerial-vehicle architecture coined as ARCog. The proposed architecture lays the groundwork for the development of a software platform aligned with the requirements of the state-of-the-art technology in the field. The system is designed to provide high-level decision-making. Experiments prove that ARCog works correctly in its target scenario.

For acquiring a broad view in an unknown environment, we proposed a control strategy based on the Bézier curve for the snake robot raising its head. Then, an improved discretization method was developed to accommodate the backbone curves with more complex shapes. Besides, in order to determine the condition of using the improved discretization method, energy of framed space curve is introduced originally to estimate the shape complexity of the backbone curve. At last, based on degree elevation of the Bézier curve, an obstacle avoidance strategy of the head-raising motion was proposed and validated through simulation.

This paper proposes a novel laser beam tracking mechanism for a mobile target robot that is used in shooting ranges. Compared with other traditional tracking mechanisms and modules, the proposed laser beam tracking mechanism is more flexible and low cost in use. The mechanical design and the working principle of the tracking module are illustrated, and the complete control system of the mobile target robot is introduced in detail. The tracking control includes two main steps: localizing the mobile target robot with regards to the position of the laser beam and tracking the laser beam by the linear quadratic regulator (LQR). First of all, the state function of the control system is built for this tracking system; second, the control law is deduced according to the discretized state function; lastly, the stability of the control method is proved by the Lyapunov theory. The experimental results demonstrate that the Hue, Saturation, Value feature-extracting method is robust and is qualified to be used for localization in the laser beam tracking control. It is verified through experiments that the LQR method is of better performance than the conventional Proportional Derivative control in the aspect of converge time, lateral error control, and distance error control.

The design and experimental works of an autonomous robotic platform for road marks painting are presented in this paper as the first autonomous system of its kind. The whole system involves two main sub-systems, namely: an autonomous mobile robot navigation system which is used for recognizing the roads and estimating the position of road marks, and automatic road marks painting system that is attached to the mobile robot platform to control the spray of the paint on the road’s surface. The experimental results show the capability of the proposed system to perform the task of autonomous road marks painting with accuracy of ±10 cm.