Jingchuan Wang

Localizability estimation for mobile robots based on probabilistic grid map and its applications to localization

A novel approach to estimate localizability for mobile robots is presented based on probabilistic grid map (PGM). Firstly, a static localizability matrix is proposed for off-line estimation over the priori PGM. Then a dynamic localizability matrix is proposed to deal with unexpected dynamic changes. These matrices describe both localizability index and localizability direction quantitatively. The validity of the proposed method is demonstrated by experiments in different typical environments. Furthermore, two typical localization-related applications, including active global localization and pose tracking, are presented for illustrating the effectiveness of the proposed localizability estimation method.

Inspection of welding pool height from shading in pulsed GTAW with wire filler

– The control of weld penetration in gas tungsten‐arc welding (GTAW) is required for fully automated systems to overcome variations in the welding process. The surface depression of weld pool, or weld pool height, has a close relationship with width of the backside bead in the full‐penetrated weld. The purpose of this paper is to inspect the pool height., – A fast linear approach, based on shape from shading (SFS) algorithm, was employed to reconstruct a 3D shape of welding pool from a 2D image, which was obtained from a real welding pool. Then the pool height can be extracted. Furthermore, three methods were introduced to improve the above algorithm., – The reconstructed pool height was in good agreement with the real height of weld pool from experiments., – The algorithm requires a uniform reflection on the pool surface., – This method is applicable to inspect weld pool height in GTAW. It is a basis for future work on control of weld penetration., – A faster SFS algorithm has been introduced to extract weld pool height in real‐time. Moreover, the algorithm was improved to fit for extracting the surface shape of weld pool.

Formation Control of Mobile Robots Using Distributed Controller With Sampled-Data and Communication Delays

This brief presents a synchronous formation control approach using distributed controller with sampled-data and communication delay. The local information of each robot is sampled first, and then transmitted to its coupling robots through a network with communication delays, i.e., the information exchanged between coupling robots is the sampled-data with communication delays. The distributed formation controller is designed by using the synchronization approach, which enables mobile robots to maintain time-varying formations while performing a group task in a synchronous manner. A sufficient condition for formation control that can guarantee the exponential convergence of both the position errors and the synchronization errors is obtained by using the Lyapunov approach. Based on the proposed sufficient condition, an upper bound of the sampling period and the communication delay that guarantees mobile robots to converge to the desired formations can be easily obtained. Finally, the effectiveness of the proposed method is demonstrated by simulations and real experiments.

Action selection for active and cooperative global localization based on localizability estimation

In this paper we investigate the action selection problem for multiple mobile robots active and cooperative global localization in large environments. Firstly, an off-line localizability estimation approach using known probabilistic grid map (PGM) is briefly proposed and a localizability matrix is presented to describe properties of expected localization probability distribution (LPD). Based on the proposed localizability matrix, a novel on-line action selection mechanism is further presented which enables mobile robots to actively collaborate with each other and select complementary actions with redundant information exclusion. This action selection mechanism brings the lowest expected localization covariance in each localization cycle and can accelerate the converging speed of global localization. Efficiency in time complexity also ensures that the proposed method could be used in real applications. The appropriateness of our approach is demonstrated through simulations and real experiments.

Map-based localization for mobile robots in high-occluded and dynamic environments

Purpose – The purpose of this paper is to propose a localizability-based particle filtering localization algorithm for mobile robots to maintain localization accuracy in the high-occluded and dynamic environments with moving people. Design/methodology/approach – First, the localizability of mobile robots is defined to evaluate the influences of both the dynamic obstacles and prior-map on localization. Second, based on the classical two-sensor track fusion algorithm, the odometer-based proposal distribution function (PDF) is corrected, taking account of the localizability. Then, the corrected PDF is introduced into the classical PF with “roulette” re-sampling. Finally, the robot pose is estimated according to all the particles. Findings – The experimental results show that, first, it is necessary to consider the influence of the prior-map during the localization in the high-occluded and dynamic environments. Second, the proposed algorithm can maintain an accurate and robust robot pose in the high-occluded ...

An Improved Localization and Navigation Method for Intelligent Wheelchair In Narrow and Crowded Environments

Abstract JiaoLong as an intelligent wheelchair is designed to assist elders with mobility and cognitive ability impairment. This paper describes an improved localization and navigation algorithm which runs on JiaoLong. In narrow and crowded environments, the improved particle filter localization algorithm estimates the belief of laser range finder observations and odometer data. The predicted wheelchair position is gained according to the observed information and predicted model. Another focus of this paper is navigation and docking in narrow spaces; a trajectory planed method is used for docking configuration. Experiments of localization and navigation under real environments are designed to validate the system.

An adaptive sinusoidal disturbance rejection controller for single-input-single-output systems

Abstract The design of an adaptive sinusoidal disturbance rejection controller for Single-Input-Single-Output (SISO) systems is presented in this paper. Sinusoidal disturbance rejection problems exist in industry applications such as velocity ripples in a CNC milling machine. The controller is first developed based on the Internal Model Principle (IMP) and the polezero placement technique, then a Gain Scheduled (GS) robust Two-Degree-of-Freedom (2DOF) regulator is constructed to eliminate the sinusoidal disturbances with known frequencies and to achieve a desirable tracking response simultaneously, but without estimating the amplitude and the phase values of the sinusoidal disturbances. Using the small gain theorem, the system stability radius is obtained for n slow time varying sinusoidal disturbances. Finally, the proposed controller is applied to eliminate the torque and velocity ripples in the Alternating Current (AC) Permanent Magnet (PM) motor control systems.

Image-Based Visual Servoing of a Quadrotor Using Virtual Camera Approach

In this paper, an image-based visual servoing control law is proposed for a quadrotor unmanned aerial vehicle using an on-board monocular camera and an inertial measurement unit sensor. Based on the perspective projection model, suitable image features are defined on a rotated image plane called virtual image plane, thus a decoupled image feature dynamics is achieved. Then, a translational velocity observer is presented using these image features. The image feature dynamics and quadrotor dynamics are combined to derive a nonlinear controller. The controller is based on backstepping technique to account for the underactuation of the quadrotor. The image-based visual servoing controller only needs three point features, which make it useable in general environment. The closed-loop system is proved globally asymptotic stable by means of Lyapunov analysis. Computer simulations that regulate a quadrotor to a desired position with respect to (w.r.t.) four points lying on a horizontal plane and three points lying on a full rotated slope are conducted separately. Smooth and efficient trajectories are obtained both in virtual image plane and Cartesian space. Finally, experimental tests including pushing and pulling the visual target are conducted to verify the validity and robustness of the proposed controller. The proposed control law regulates the quadrotor to a desired position, defined by desired image, from an unknown initial position, which can be used in monitoring, landing, and other applications.

Multilayer Matching SLAM for Large-Scale and Spacious Environments

In large-scale and spacious environments, keeping a reliable data association and reducing computational complexity are challenges for the implementation of Simultaneous Localization and Mapping (SLAM). Focused on these problems, a multilayer-matching-based incremental SLAM algorithm is proposed in this article. In this algorithm, SLAM is simplified as a problem composed of a least-square-based optimization problem and data association. Then, it is solved in two steps. Firstly, a multilayer matching method is applied to deal with the data-association problem. Both matching between observation and local map and matching between different local maps are carried out. The uncertainty of the results-matching is described by the Fisher information matrix. Secondly, the robot pose is optimized through an incremental QR decomposition method. This algorithm effectively avoids the local minima caused by the limited observation information, and can build a consistent map of the environment. Meanwhile, the characters (hierarchical and incremental) of the proposed algorithm ensure low computational complexity. Experiments on simulation environments and two kinds of real environments with different sparse features verify that the algorithm is applicable for real-time application in large-scale and spacious environments.

A control system of driver assistance and human following for smart wheelchair

Driver assistance is one of the major tasks on smart wheelchair development. However, human following is also necessary in real application. In this paper, a control system of driver assistance and human following for smart wheelchair is presented. Driver assistance can keep the wheelchair from stairs falling and obstacle collision when the user is driving the wheelchair in complex environments with unknown obstacles. Human following can guarantee the wheelchair to follow the user with a suitable distance when the user wants to walk along by himself. The target occlusion problem caused by obstacle avoidance during human following can also be effectively solved by the use of odometry data. Both the driver assistance and human following are based on shared control strategy. And since the sensor used is ultrasound, instead of LRF, the proposed system is low-cost and can be easily implemented in real applications. The system is developed and tested on JiaoLong smart wheelchair. Experiment results show that the proposed system can improve users driving ability in driver assistance task and it can control the wheelchair to keep a suitable distance with the target human. And it can effectively handle the target occlusion problem when it has to avoid obstacle in human following task.