Journal of Robotics

The flight of unmanned aerial vehicles (UAVs) has numerous associated challenges. Small size is the major reason of their sensitivity towards turbulence restraining them from stable flight. Turbulence alleviation strategies of birds have been explored in recent past in detail to sort out this issue. Besides using primary and secondary feathers, birds also utilize covert feathers deflection to mitigate turbulence. Motivated from covert feathers of birds, this paper presents biologically inspired gust mitigation system (GMS) for a flapping wing UAV (FUAV). GMS consists of electromechanical (EM) covert feathers that sense the incoming gust and mitigate it through deflection of these feathers. A multibody model of gust-mitigating FUAV is developed appending models of the subsystems including rigid body, propulsion system, flapping mechanism, and GMS-installed wings using bond graph modeling approach. FUAV without GMS and FUAV with the proposed GMS integrated in it are simulated in the presence of vertical gust, and results’ comparison proves the efficacy of the proposed design. Furthermore, agreement between experimental results and present results validates the accuracy of the proposed design and developed model.

Aiming at the problems of slow convergence, easy to fall into local optimum, and poor smoothness of traditional ant colony algorithm in mobile robot path planning, an improved ant colony algorithm based on path smoothing factor was proposed. Firstly, the environment map was constructed based on the grid method, and each grid was marked to make the ant colony move from the initial grid to the target grid for path search. Then, the heuristic information is improved by referring to the direction information of the starting point and the end point and combining with the turning angle. By improving the heuristic information, the direction of the search is increased and the turning angle of the robot is reduced. Finally, the pheromone updating rules were improved, the smoothness of the two-dimensional path was considered, the turning times of the robot were reduced, and a new path evaluation function was introduced to enhance the pheromone differentiation of the effective path. At the same time, the Max-Min Ant System (MMAS) algorithm was used to limit the pheromone concentration to avoid being trapped in the local optimum path. The simulation results show that the improved ant colony algorithm can search the optimal path length and plan a smoother and safer path with fast convergence speed, which effectively solves the global path planning problem of mobile robot.

How to quickly and accurately judge the maturity of muskmelon is very important to consumers and muskmelon sorting staff. This paper presents a novel approach to solve the difficulty of muskmelon maturity stage classification in greenhouse and other complex environments. The color characteristics of muskmelon were used as the main feature of maturity discrimination. A modified 29-layer ResNet was applied with the proposed two-way data augmentation methods for the maturity stages of muskmelon classification using indoor and outdoor datasets to create a robust classification model that can generalize better. The results showed that code data augmentation which is the first way caused more performance degradation than input image augmentation—the second way. This established the effectiveness of the code data augmentation compared to image augmentation. Nevertheless, the two-way data augmentations including the combination of outdoor and indoor datasets to create a classification model revealed an excellent performance of F₁ score ∼99%, and hence the model is applicable to computer-based platform for quick muskmelon stages of maturity classification.

It is easy to realize that most robots do not move to the desired endpoint (Tool Center Point (TCP)) using high-resolution noncontact instrumentation because of manufacturing and assembly errors, transmission system errors, and mechanical wear. This paper presents a robot calibration solution by changing the endpoint trajectories while maintaining the robot’s control system and device usages. Two independent systems to measure the endpoint positions, the robot encoder and a noncontact measuring system with a high-resolution camera, are used to determine the endpoint errors. A new trajectory based on the measured errors will be built to replace the original trajectory. The results show that the proposed method can significantly reduce errors; moreover, this is a low-cost solution and easy to apply in practice and calibration can be done cyclically. The only requirement for this method is a noncontact measuring device with high-resolution and located independently with the robot in calibration.

When the two arms of the robot are transporting the heavy loads together, a new parallel mechanism is formed. The actuator input selection and optimization of the parallel mechanism are basic and important problems in mechanism research. In this paper, a 2-RPPPS dual-arm robot is taken as the research object. Firstly, based on the screw theory and input selection principle, 158 reasonable schemes are obtained. Then, an evaluation mechanism is established to screen out the schemes that do not conform to the input selection principle. Then, the end effector of the parallel mechanism moves along two different trajectories. Using the particle swarm optimization algorithm, the inverse kinematics solution of each trajectory is obtained, and the velocity and acceleration of each actuator under different trajectories are obtained. Finally, the motion stability of each actuator is evaluated, and the best scheme is selected. The results show that the best input scheme can be selected according to different trajectories, so as to improve the performance of the parallel mechanism. To the authors’ knowledge, no one has done any research on selecting the appropriate input scheme according to the trajectory of the end effector.

Tip-over stability analysis is critical for the success of mobile manipulation of the dual arm, especially in the cases that the dual arm or the mobile platform moves rapidly. Due to strong dynamics coupling between the dual arm and mobile platform, online evaluation of dynamic stability of the mobile dual-arm robot still remains challenging. This paper presents an improved tip-over moment stability criterion dealing with the dual arm and mobile platform interaction and proposes an algorithm for calculating the tip-over stability margin of the arm end in the workspace to analyze the dynamic stability of the wheeled mobile dual-arm robot. The simulations on a four-wheeled mobile dual-arm robot validate the correctness and feasibility of the proposed method.