Unknown Obstacle Environment Research Articles

Adaptive virtual leader–leader–follower based formation switching for multiple autonomous tracked mobile robots in unknown obstacle environments

This article investigates the formation switching problem of a group of autonomous tracked mobile robots (ATMRs) traveling in unknown obstacle environments. Firstly, a novel formation structure model of virtual leader–leader–follower is designed, where the leader tracks the virtual leader determined by a reference trajectory, while the followers track their desired positions dictated by the virtual leader. Subsequently, a dynamic optimization formation switching strategy is developed, in which the leader calculates a formation adjustment factor in real-time to dynamically adjust the formation parameters according to the environmental constraints. Furthermore, a comprehensive performance evaluation index system is presented to assess formation switching efficiency, leveraging the inherent simplicity of the ATMR’s kinematics. Finally, extensive numerical simulations and physical experiments are carried out to validate the effectiveness of the proposed strategies.

Unmanned mobile robot in unknown obstacle environments for multi switching control tracking using adaptive nonlinear sliding mode control method

This paper focuses on a wheeled mobile robot that utilizes the Adaptive Nonlinear Sliding mode control technique for trajectory tracking and obstacle avoidance control. A parallel wheeled differential drive Mobile robot’s trajectory tracking control problem is investigated. For diverse initial conditions, the robot must follow a given course to reach it’s destination. To monitor and identify the obstacles in the path, an obstacle micro-controller is fixed to decide quick crash avoidance and follow the obstacle limit at a predetermined distance. It depends on the robot’s vector connections. An Adaptive Nonlinear Sliding Mode (ANSM) control concept is used for continuous trajectory tracking or object monitoring in the path to avoid it. A Lapunov function control gives stability to each controller. The proposed simulation results demonstrate that the mobile robot can be applied to guarantee its protected development in an obscure obstacle environment. In detail, the proposed control gives another, more straightforward methodology with application esteems for tracking critical thinking in an obscure obstacle environment. Finally, based on these above characteristics, the proposed control strategy’s efficiency, simplicity, and accuracy prove. The steady-state error and mean squared error of the proposed ANSM are 6% and 0.07db, respectively.

A Hybrid Multi-Target Path Planning Algorithm for Unmanned Cruise Ship in an Unknown Obstacle Environment.

To solve the problem of traversal multi-target path planning for an unmanned cruise ship in an unknown obstacle environment of lakes, this study proposed a hybrid multi-target path planning algorithm. The proposed algorithm can be divided into two parts. First, the multi-target path planning problem was transformed into a traveling salesman problem, and an improved Grey Wolf Optimization (GWO) algorithm was used to calculate the multi-target cruise sequence. The improved GWO algorithm optimized the convergence factor by introducing the Beta function, which can improve the convergence speed of the traditional GWO algorithm. Second, based on the planned target sequence, an improved D* Lite algorithm was used to implement the path planning between every two target points in an unknown obstacle environment. The heuristic function in the D* Lite algorithm was improved to reduce the number of expanded nodes, so the search speed was improved, and the planning path was smoothed. The proposed algorithm was verified by experiments and compared with the other four algorithms in both ordinary and complex environments. The experimental results demonstrated the strong applicability and high effectiveness of the proposed method.

Auction-Based Consensus of Autonomous Vehicles for Multi-Target Dynamic Task Allocation and Path Planning in an Unknown Obstacle Environment

The autonomous vehicle technology has recently been developed rapidly in a wide variety of applications. However, coordinating a team of autonomous vehicles to complete missions in an unknown and changing environment has been a challenging and complicated task. We modify the consensus-based auction algorithm (CBAA) so that it can dynamically reallocate tasks among autonomous vehicles that can flexibly find a path to reach multiple dynamic targets while avoiding unexpected obstacles and staying close as a group as possible simultaneously. We propose the core algorithms and simulate with many scenarios empirically to illustrate how the proposed framework works. Specifically, we show that how autonomous vehicles could reallocate the tasks among each other in finding dynamically changing paths while certain targets may appear and disappear during the movement mission. We also discuss some challenging problems as a future work.

A Multi-Switching Tracking Control Scheme for Autonomous Mobile Robot in Unknown Obstacle Environments

The obstacle avoidance control of mobile robots has been widely investigated for numerous practical applications. In this study, a control scheme is presented to deal with the problem of trajectory tracking while considering obstacle avoidance. The control scheme is simplified into two controllers. First, an existing trajectory tracking controller is used to track. Next, to avoid the possible obstacles in the environment, an obstacle avoidance controller, which is used to determine the fastest collision avoidance direction to follow the boundary of the obstacle at a constant distance, is proposed based on vector relationships between the robot and an obstacle. Two controllers combined via a switch strategy are switched to perform the task of trajectory tracking or obstacle avoidance. The stability of each controller in the control scheme is guaranteed by a Lyapunov function. Finally, several simulations are conducted to evaluate the proposed control scheme. The simulation results indicate that the proposed scheme can be applied to the mobile robot to ensure its safe movement in unknown obstacle environments.

A Practical Leader–Follower Tracking Control Scheme for Multiple Nonholonomic Mobile Robots in Unknown Obstacle Environments

This brief addresses the leader–follower (L-F) tracking control problem for multiple nonholonomic mobile robots in unknown obstacle environments. Unlike most of the existing approaches investigating similar problems, a series of practical issues is considered and tackled in the proposed scheme. For leader tracking, a class of bounded barrier functions are employed to formulate distance and bearing angle constraints introduced by sensor limitations and L-F collision avoidance requirement. To ensure robot safety in unknown environments, a multiregion obstacle avoidance algorithm is proposed which prioritizes different control objectives in different regions. This brief also studies the leader-loss situation, which may be caused by illumination variation, motion blurring, or visual occlusion by obstacles. To deal with this case, a fault-tolerant strategy is designed to drive $F$ to the place where $L$ was lost immediately. The control scheme proposed in the brief is primarily designed for a communication-free environment where only local state measurements are available. Furthermore, it has control input constraints explicitly taken into account. Real robot experiment has been performed to validate the proposed method.

Vision-Based Flexible Leader–Follower Formation Tracking of Multiple Nonholonomic Mobile Robots in Unknown Obstacle Environments

This brief investigates the flexible leader–follower formation tracking problem for a group of nonholonomic mobile robots, while most of the formation control related work in the literature focuses on the rigid formation. The flexible formation discussed in this brief is defined in curvilinear coordinates in terms of longitudinal separations between robots along the reference trajectory and lateral deviations with respect to this trajectory. Unlike the previous studies on flexible formation control, this brief is under a more challenging assumption that the global position and orientation measurements are not available. To obtain the relative pose relationships amongst robots, a stereo camera is mounted on each follower. In consideration of the fact that visual observations are noise-corrupted and intermittently available, a particle filter-based relative pose estimation approach is employed to estimate the position and orientation of the leader in the local reference frame of the follower using the polluted and discontinuous information. Also, to form a flexible formation, the leader historical trajectory is reconstructed with respect to the current local frame attached on the follower, based on which a reference point is generated. In addition, this brief considers the situation where robots operate in unknown obstacle environments. To ensure robot safety in such environments, a multiobjective control law is proposed to balance reference tracking and collision avoidance in different situations. Simulation and real-robot experiment have been performed to demonstrate the efficacy of the proposed method.

Cooperation control of multiple miniature robots in unknown obstacle environment

This article focuses on the cooperative control problem of a group of miniature mobile robots in the environment with unknown obstacles. Each robot in the group has limited sensing and communication capability. The problem is addressed by separating it into two parts. One part is the formation control of multi-robot and another is navigation control with unknown obstacles. In the first part, a flexible and fault-tolerant formation scheme is introduced. Meanwhile, the dynamic surface method is combined with backstepping sliding mode control as the tracking control law. In the navigation control part, smooth trajectory of obstacle avoidance is obtained based on limit cycle principle and distance sensor data. Finally, the effectiveness of the proposed method is verified by numerical simulations and hardware experiments carried out on the real platform.

Development of Sensor-Based Navigation for Mobile Robots Using Target Direction Sensor

Sensor-based navigation used a target direction sensor for mobile robots among unknown obstacles in work space is discussed. The advantage of target direction information is robustness of measurement error for online navigation, compared to robot location information. Convergence of navigation using target direction information is discussed. An actual sensor system using two CdS sensors to measure target direction is proposed. Using target direction information, we present a new sensor based navigation algorithm in unknown obstacle environment. The navigation algorithm is based on target direction information, unlike sensor-based motion planning algorithms based on mobile robot location information. Using a sensor-based navigation system, we conducted a navigation experiment and simulations in unknown obstacle environment.

Special Issue on Mobile Robot

Mobility, or locomotion, is as important a function for robots as manipulation. A robot can enlarge its work space by locomotion. It can also recognize its environment well with its sensors by moving around and by observing its surroundings from various directions. Much researches has been done on mobile robots and the research appears to be mature. Research activity on robot mobility is still very active; for example, 22% of the sessions at ICRA'98 - the International Conference on Robotics and Automation - and 24% of the sessions at IROS'98 - the International Conference on Intelligent Robots and Systems - dealt with issues directly related to mobile robots. One of the main reasons may be that intelligent mobile robots are thought to be the closest position to autonomous robot applications. This special issue focuses on a variety of mobile robot research from mobile mechanisms, localization, and navigation to remote control through networks. The first paper, entitled ""Control of an Omnidirectional Vehicle with Multiple Modular Steerable Drive Wheels,"" by M. Hashimoto et al., deals with locomotion mechanisms. They propose an omnidirectional mobile mechanism consisting of modular steerable drive wheels. The omnidirectional function of mobile mechanisms will be an important part of the human-friendly robot in the near future to realize flexible movements in indoor environments. The next three papers focus on audiovisual sensing to localize and navigate a robot. The second paper, entitled ""High-Speed Measurement of Normal Wall Direction by Ultrasonic Sensor,"" by A. Ohya et al., proposes a method to measure the normal direction of walls by ultrasonic array sensor. The third paper, entitled ""Self-Position Detection System Using a Visual-Sensor for Mobile Robots,"" is written by T. Tanaka et al. In their method, the position of the robot is decided by measuring marks such as name plates and fire alarm lamps by visual sensor. In the fourth paper, entitled ""Development of Ultra-Wide-Angle Laser Range Sensor and Navigation of a Mobile Robot in a Corridor Environment,"" written by Y Ando et al., a very wide view-angle sensor is realized using 5 laser fan beam projectors and 3 CCD cameras. The next three papers discussing navigation problems. The fifth paper, entitled ""Autonomous Navigation of an Intelligent Vehicle Using 1-Dimensional Optical Flow,"" by M. Yamada and K. Nakazawa, discusses navigation based on visual feedback. In this work, navigation is realized by general and qualitative knowledge of the environment. The sixth paper, entitled ""Development of Sensor-Based Navigation for Mobile Robots Using Target Direction Sensor,"" by M. Yamamoto et al., proposes a new sensor-based navigation algorithm in an unknown obstacle environment. The seventh paper, entitled ""Navigation Based on Vision and DGPS Information for Mobile Robots,"" S. Kotani et al., describes a navigation system for an autonomous mobile robot in an outdoor environment. The unique point of their paper is the utilization of landmarks and a differential global positioning system to determine robot position and orientation. The last paper deals with the relationship between the mobile robot and computer networks. The paper, entitled ""Direct Mobile Robot Teleoperation via Internet,"" by K. Kawabata et al., proposes direct teleoperation of a mobile robot via the Internet. Such network-based robotics will be an important field in robotics application. We sincerely thank all of the contributors to this special issue for their cooperation from the planning stage to the review process. Many thanks also go to the reviewers for their excellent work. We will be most happy if this issue aids readers in understanding recent trends in mobile robot research and furthers interest in this research field.