A Deformable Configuration Planning Framework for a Parallel Wheel-Legged Robot Equipped with Lidar

RobotSDF: Implicit Morphology Modeling for the Robotic Arm

The expression of robot arm morphology is a critical foundation for achieving effective motion planning and collision avoidance in robotic systems. Traditional geometry-based approaches usually suffer from the contradiction between the high demand for computing resources for fine expression and the insufficient detail expression caused by the pursuit of efficiency. The signed distance function addresses these drawbacks due to its ability to handle complex and arbitrary shapes and lower computational requirements. However, conventional robotic morphology methods based on the signed distance function often face challenges when the robot moves dynamically, since robots with different postures are modeled as independent individuals but the postures of robots are infinite. In this paper, we introduce RobotSDF, an implicit morphology modeling approach that can express the robot shape of arbitrary posture precisely. Instead of depicting a whole model of the robot arm, RobotSDF models the robot morphology as integrated implicit joint models driven by joint configurations. In this approach, the dynamic shape change process of the robot is converted into the coordinate transformations of query points within each joint's coordinate system. Experimental results with the Elfin robot demonstrate that RobotSDF can accurately depict robot shapes across different postures up to the millimeter level, which exhibits 38.65% and 66.24% improvement over the Neural-JSDF and configuration space distance field algorithms, respectively, in representing robot morphology. We further verified the efficiency of RobotSDF through collision avoidance in both simulation and actual human-robot collaboration experiments.

Multi-Dataset Hyper-CNN for Hyperspectral Image Segmentation of Remote Sensing Images

This research paper presents novel condensed CNN architecture for the recognition of multispectral images, which has been developed to address the lack of attention paid to neural network designs for multispectral and hyperspectral photography in comparison to RGB photographs. The proposed architecture is able to recognize 10-band multispectral images and has fewer parameters than popular deep designs, such as ResNet and DenseNet, thanks to recent advancements in more efficient smaller CNNs. The proposed architecture is trained from scratch, and it outperforms a comparable network that was trained on RGB images in terms of accuracy and efficiency. The study also demonstrates the use of a Bayesian variant of CNN architecture to show that a network able to process multispectral information greatly reduces the uncertainty associated with class predictions in comparison to standard RGB images. The results of the study are demonstrated by comparing the accuracy of the network’s predictions to the images.

Design and Research of All-Terrain Wheel-Legged Robot

Aiming at the crossing problem of complex terrain, to further improve the ability of obstacles crossing, this paper designs and develops an all-terrain wheel-legged hybrid robot (WLHR) with strong adaptability to the environment. According to the operation requirements in different road conditions, the robot adopts a wheel and leg compound structure, which can realize the transformation of wheel movement and leg movement to adjust its motion state. The straight and turning process of the robot is analyzed theoretically, the kinematics model is established and solved, and obstacle crossing analysis is carried out by establishing the mathematical model of front wheel obstacle crossing when the robot meets obstacles. To verify the analysis results, ADAMS software is used to simulate and analyze the process of robot running on the complex road surface and obstacles-crossing. Finally, a theoretical prototype is made to verify its feasibility. Theoretical analysis and experimental results show that the designed WLHR is feasible and has the stability of the wheeled mechanism and the higher obstacle crossing ability of the legged mechanism so that the robot can adapt to a variety of complex road conditions.

A Dynamic Motion Analysis of a Six-Wheel Ground Vehicle for Emergency Intervention Actions

To protect the personnel of the intervention units operating in high-risk areas, it is necessary to introduce (autonomous/semi-autonomous) robotic intervention systems. Previous studies have shown that robotic intervention systems should be as versatile as possible. Here, we focused on the idea of a robotic system composed of two vectors: a carrier vector and an operational vector. The proposed system particularly relates to the carrier vector. A simple analytical model was developed to enable the entire robotic assembly to be autonomous. To validate the analytical-numerical model regarding the kinematics and dynamics of the carrier vector, two of the following applications are presented: intervention for extinguishing a fire and performing measurements for monitoring gamma radiation in a public enclosure. The results show that the chosen carrier vector solution, i.e., the ground vehicle with six-wheel drive, satisfies the requirements related to the mobility of the robotic intervention system. In addition, the conclusions present the elements of the kinematics and dynamics of the robot.

Suboptimal Omnidirectional Wheel Design and Implementation

The optimal design of an omnidirectional wheel is usually focused on the minimization of the gap between the free rollers of the wheel in order to minimize contact discontinuities with the floor in order to minimize the generation of vibrations. However, in practice, a fast, tall, and heavy-weighted mobile robot using optimal omnidirectional wheels may also need a suspension system in order to reduce the presence of vibrations and oscillations in the upper part of the mobile robot. This paper empirically evaluates whether a heavy-weighted omnidirectional mobile robot can take advantage of its passive suspension system in order to also use non-optimal or suboptimal omnidirectional wheels with a non-optimized inner gap. The main comparative advantages of the proposed suboptimal omnidirectional wheel are its low manufacturing cost and the possibility of taking advantage of the gap to operate outdoors. The experimental part of this paper compares the vibrations generated by the motion system of a versatile mobile robot using optimal and suboptimal omnidirectional wheels. The final conclusion is that a suboptimal wheel with a large gap produces comparable on-board vibration patterns while maintaining the traction and increasing the grip on non-perfect planar surfaces.