MS23D: A 3D object detection method using multi-scale semantic feature points to construct 3D feature layer.

LiDAR point clouds can effectively depict the motion and posture of objects in three-dimensional space. Many studies accomplish the 3D object detection by voxelizing point clouds. However, in autonomous driving scenarios, the sparsity and hollowness of point clouds create some difficulties for voxel-based methods. The sparsity of point clouds makes it challenging to describe the geometric features of objects. The hollowness of point clouds poses difficulties for the aggregation of 3D features. We propose a two-stage 3D object detection framework, called MS23D. (1) We propose a method using voxel feature points from multi-branch to construct the 3D feature layer. Using voxel feature points from different branches, we construct a relatively compact 3D feature layer with rich semantic features. Additionally, we propose a distance-weighted sampling method, reducing the loss of foreground points caused by downsampling and allowing the 3D feature layer to retain more foreground points. (2) In response to the hollowness of point clouds, we predict the offsets between deep-level feature points and the object's centroid, making them as close as possible to the object's centroid. This enables the aggregation of these feature points with abundant semantic features. For feature points from shallow-level, we retain them on the object's surface to describe the geometric features of the object. To validate our approach, we evaluated its effectiveness on both the KITTI and ONCE datasets.

Application of the Improved Rapidly Exploring Random Tree Algorithm to an Insect-like Mobile Robot in a Narrow Environment.

When intelligent mobile robots perform global path planning in complex and narrow environments, several issues often arise, including low search efficiency, node redundancy, non-smooth paths, and high costs. This paper proposes an improved path planning algorithm based on the rapidly exploring random tree (RRT) approach. Firstly, the target bias sampling method is employed to screen and eliminate redundant sampling points. Secondly, the adaptive step size strategy is introduced to address the limitations of the traditional RRT algorithm. The mobile robot is then modeled and analyzed to ensure that the path adheres to angle and collision constraints during movement. Finally, the initial path is pruned, and the path is smoothed using a cubic B-spline curve, resulting in a smoother path with reduced costs. The evaluation metrics employed include search time, path length, and the number of sampling nodes. To evaluate the effectiveness of the proposed algorithm, simulations of the RRT algorithm, RRT-connect algorithm, RRT* algorithm, and the improved RRT algorithm are conducted in various environments. The results demonstrate that the improved RRT algorithm reduces the generated path length by 25.32% compared to the RRT algorithm, 26.42% compared to the RRT-connect algorithm, and 4.99% compared to the RRT* algorithm. Moreover, the improved RRT algorithm significantly improves the demand for reducing path costs. The planning time of the improved RRT algorithm is reduced by 64.96% compared to that of the RRT algorithm, 40.83% compared to that of the RRT-connect algorithm, and 27.34% compared to that of the RRT* algorithm, leading to improved speed. These findings indicate that the proposed method exhibits a notable improvement in the three crucial evaluation metrics: sampling time, number of nodes, and path length. Additionally, the algorithm performed well after undergoing physical verification with an insect-like mobile robot in a real environment featuring narrow elevator entrances.

Computed torque control and force analysis for mechanical leg with variable rotation axis powered by servo pneumatic muscle.

It is difficult for a humanoid leg driven by two groups of antagonistic pneumatic muscles (PMs) to achieve a flexible humanoid gait, and its inherent strong coupling nonlinear characteristics make it hard to achieve good tracking performance in a large range of motion. Therefore, a four-bar linkage bionic knee joint structure with a variable axis and a double closed-loop servo position control strategy based on computed torque control are designed to improve anthropomorphic characteristics and the dynamic performance of the bionic mechanical leg powered by servo pneumatic muscle (SPM). Firstly, the relationship between the joint torque, the initial jump angle and the bounce height of the mechanical leg is established, and then we design a double-joint PM bionic mechanical leg containing a four-bar linkage mechanism of the knee joint. Secondly, a cascade position control strategy is developed, which consists of the outer position loop and the inner contraction force loop, and the mapping relationship is designed between joint torque and antagonistic PM contraction force. Finally, we further project bounce action timing of mechanical leg to realize the periodic jumping movement of the mechanical leg, and simulation and physical experiments of the real-style machine platform have been provided to demonstrate the effectiveness of the designed SPM controller.

Modeling Contact Stiffness of Soft Fingertips for Grasping Applications.

Soft fingertips have distinct intrinsic features that allow robotic hands to offer adjustable and manageable stiffness for grasping. The stability of the grasp is determined by the contact stiffness between the soft fingertip and the object. Within this work, we proposed a line vector representation method based on the Winkler Model and investigated the contact stiffness between soft fingertips and objects to achieve control over the gripping force and fingertip displacement of the gripper without the need for sensors integrated in the fingertip. First, we derived the stiffness matrix of the soft fingertip, analyzed the contact stiffness, and constructed the global stiffness matrix; then, we established the grasp stiffness matrix based on the contact stiffness model, allowing for the analysis and evaluation of the soft fingertip's manipulating process. Finally, our experiment demonstrated that the variation in object orientation caused by external forces can indicate the contact force status between the fingertip and the object. This contact force status is determined by the contact stiffness. The position error between the theoretical work and tested data was less than 9%, and the angle error was less than 5.58%. The comparison between the theoretical contact stiffness and the experimental results at the interface indicate that the present model for the contact stiffness is appropriate and the theoretical contact stiffness is consistent with the experiment data.

Research on smooth path planning method based on improved ant colony algorithm optimized by Floyd algorithm.

Aiming at the problems of slow convergence and easy fall into local optimal solution of the classic ant colony algorithm in path planning, an improved ant colony algorithm is proposed. Firstly, the Floyd algorithm is introduced to generate the guiding path, and increase the pheromone content on the guiding path. Through the difference in initial pheromone, the ant colony is guided to quickly find the target node. Secondly, the fallback strategy is applied to reduce the number of ants who die due to falling into the trap to increase the probability of ants finding the target node. Thirdly, the gravity concept in the artificial potential field method and the concept of distance from the optional node to the target node are introduced to improve the heuristic function to make up for the fallback strategy on the convergence speed of the algorithm. Fourthly, a multi-objective optimization function is proposed, which comprehensively considers the three indexes of path length, security, and energy consumption and combines the dynamic optimization idea to optimize the pheromone update method, to avoid the algorithm falling into the local optimal solution and improve the comprehensive quality of the path. Finally, according to the connectivity principle and quadratic B-spline curve optimization method, the path nodes are optimized to shorten the path length effectively.

Observer-based state feedback H∞ control for offshore steel jacket structures under denial-of-service attacks.

This article focuses on observer-based state feedback H∞ control for a jacket structure against DoS attacks and external wave loads. First, a networked model of the structure is formulated as a switched delay system, in which DoS attacks and network-induced delays are considered simultaneously. A matching switched observer is developed for estimating states of the networked jacket structure system. Then, some new sufficient conditions are provided for the observer-based networked H∞ controller for the resultant switched system. Finally, it is shown from several case studies that the provided mechanism can maintain desired performance of the jacket structure against attacks and wave loads. In addition, the developed control schemes can save the control cost significantly.

Optimal path generation in scala tympani and path planning for robotic cochlear implant of perimodiolar electrode.

In this study, a new idea of the optimal path generation method was proposed and a path planning strategy for robotic cochlear implant of perimodiolar electrode was designed. The centerline of scala tympani channel was taken as the optimal implant path of the perimodiolar electrode, which aimed to reduce the damage of the electrode to the cochlea during implantation. First, the three-dimensional cochlear model was reconstructed based on the micro-computed tomography images of cochlea, and it was re-segmented to obtain the cross sections of the scala tympani at different angles. Then, the image processing method was used to determine the central point of the scala tympani cross sections. The cubic B-spline interpolation method was used to fit these discrete central points to generate the optimal path. Finally, the coordinate information of the optimal path was combined with the stylet extraction state of perimodiolar electrode to conduct the path planning for robotic cochlear implant, and the result was sent to the robot for kinematic inverse solution to obtain the robot motion trajectory. The robotic cochlear implant experiment was performed with the model of scala tympani. The results showed that the maximum implant force based on path planning was 0.084 N, and the maximum implant force without path planning was 0.134 N. The optimal path generation and the path planning method effectively help to reduce the damage of the electrode to the cochlea.

Multi-rigid-body modeling and simulation of perimodiolar cochlear electrode arrays.

This study presented a method that decomposes perimodiolar electrodes into multi-rigid bodies for the study on the shape variation of cochlear perimodiolar electrode. The coordinates of electrode array were obtained by capturing the shape varying image of the perimodiolar electrodes with the stylet extracted. Subsequently, the increment of the angle variation and the length of each link were obtained. Fourier compensation fitting method was developed using the three fitting methods to compare and analyze the increment of the angle variation of the perimodiolar electrode multi-rigid model. This can not only ensure that the initial angle of the joint is consistent with the actual angle of the perimodiolar electrode, but also fully reflect the varying trend of the joint angle of the multi-rigid model of the perimodiolar electrode. The simulation of the shape variation of the perimodiolar electrode multi-rigid-body model was performed using this method in the ADAMS simulation platform. According to the simulation results, the precise and continuous shape variation of perimodiolar electrodes can be obtained using this method.

[Study on thinning to Robinia pseudoacacia forest on the Loess Plateau].

Radiation, temperature and soil moisture in the forests, the biodiversity and productivity of understory plants, and the growth of trees among 3 thinned 9-year-old Robinia pseudoacacia forests (735 individuals.hm-2, 1110 individuals.hm-2, and 1480 individuals.hm-2) and non-thinning forest (2220 individuals.hm-2) were analyzed comparatively. The results showed that thinning could improve growing condition of trees and understory plants, so that the biodiversity and biomass of understory plants and producing ability of trees were increased. When the remaining density was 1110 individuals.hm-2, the soil moisture was increased by 40% comparing with the non-thinning forest in whole growing seasons. The biodiversity and biomass of understory plants and productivity of trees were increased significantly. If the thinning intensity were increased continuously, the growth of understory plants and trees would reach the maximum and not increase any longer. Therefore, the thinning intensity with remaining density of 1110 individuals.hm-2 was optimum for black locust forest in this region.