Simultaneous Localization and Mapping (SLAM) is one of the fundamental capabilities for intelligent mobile robots to perform state estimation in unknown environments. However, most visual SLAM systems rely on the static scene assumption and consequently have severely reduced accuracy and robustness in dynamic scenes. Moreover, the metric maps constructed by many systems lack semantic information, so the robots cannot understand their surroundings at a human cognitive level. In this paper, we propose SG-SLAM, which is a real-time RGB-D semantic visual SLAM system based on the ORB-SLAM2 framework. First, SG-SLAM adds two new parallel threads: an object detecting thread to obtain 2D semantic information and a semantic mapping thread. Then, a fast dynamic feature rejection algorithm combining semantic and geometric information is added to the tracking thread. Finally, they are published to the ROS system for visualization after generating 3D point clouds and 3D semantic objects in the semantic mapping thread. We performed an experimental evaluation on the TUM dataset, the Bonn dataset, and the OpenLORIS-Scene dataset. The results show that SG-SLAM is not only one of the most real-time, accurate, and robust systems in dynamic scenes, but also allows the creation of intuitive semantic metric maps.

Aiming at the problem of water quality monitoring, this paper presents a method of biological water quality monitoring based on TLD (Tracking-Learning-Detection) framework and XGBoost (eXtreme Gradient Boosting). Firstly, under the framework of TLD, an independent tracking system is designed; TLD captures 3D coordinate information of fish based on video and calculates the behavior of fish movement parameters which can reflect the change of water quality via processing the coordinate information of the fish body. The data of coordinate information will be more prominent via the data processing. The integration of all built XGBoost water quality monitoring model which is based on characteristic parameters; the model was used to analyze and evaluate fish behavior parameters under unknown water quality to achieve the purpose of water quality monitoring.

Active compliance control represents a pivotal technique for managing the interplay between forces and positions. This article proposes an adaptive approach based on an identified model for variable trajectory control. Addressing parameter redundancy in the dynamic model, we propose a simplified, friction-incorporated modeling method. Key parameters are identified through current and torque data, with three friction models designed to approximate real-world scenarios. A method for monitoring instability risks is presented, particularly effective when the mass difference between the manipulator and the mobile platform is relatively small. It monitors imprudent power output, reducing risks such as overturning. Finally, within system safety constraints, an impedance model is designed to manage the relationship between external forces and position in Cartesian space. This model extends the range of motion to counteract external force influence, utilizing a trajectory modulation technique. Additionally, a trajectory tracking controller based on super-twisting sliding mode control is designed, and the stability of the control system is analyzed. Experimental validation confirms the efficacy of the proposed methodology.

Increasing demand for mobile manipulators in fields requiring high-precision tasks has introduced new requirements regarding their kinematic accuracy. Pose measurement of the mobile manipulator is a crucial method to improve the absolute positioning accuracy of the robot. To solve the pose estimation of the mobile manipulator, we propose a space measurement method based on visual marks and an interactive filtering method to improve the stability of measurement results. Firstly, the kinematics and dynamics of the mobile manipulator are analyzed, and the mathematical expression of the model is obtained to obtain the theoretical trajectory. Secondly, a visual marker based on pyramid hierarchy is proposed, which can adapt to scenes with significant distance scale changes. A visual marker of a regular 12-face is designed, the marker of each face is uniquely coded to ensure that multiple markers can be captured at the same time under a single viewing angle, and geometric relations determine the distance and pose of the end. We propose a filtering method considering the correlation of historical data to improve the stability and accuracy of measurement data. The matching degree of the filter motion mode is improved through the Pearson coefficient relationship between the filtered data in the current period and the historical data. In this paper, several experiments verify the method’s effectiveness. The repeatability of the measurement can reach 0.75mm, and the mean error(MAV)is 0.009mm. The noise test proves the anti-interference ability of the filtering method. The new filtering method has excellent performance on various tracking tracks. All experiments show that the method proposed in this paper has a good measurement effect and is a low-cost, convenient, and efficient method to solve the pose estimation and precise trajectory error analysis of mobile manipulators.

The mobile manipulator is a floating base structure with wide space operability. An integrated mechanical device for mobile operation is formed through the organic combination of the mobile platform and multi-axis manipulator. This paper presents a general kinematic modeling method for mobile manipulators and gives the relevant derivation of the dynamic model. Secondly, the null-space composition of the mobile manipulator is analyzed, the task space is divided, and a variety of task-switching criteria are designed. Finally, a hybrid control model combining dynamic feedback and synovial control based on dynamic parameter identification is designed, and stability proof is given. The theoretical method is also verified by the experimental platform. The proposed method can effectively improve the control accuracy of the mobile manipulator, and the hybrid control method can effectively control the output torque to reach the ideal state.