Dynamic obstacle avoidance mobile robot. As the study progresses, the above dynamic path .
Dynamic obstacle avoidance mobile robot The proposed method uses the information of the obstacle’s Obstacle avoidance is a significant skill not only for mobile robots but also for robot manipulators working in unstructured environments. Recent works have shown the power of deep reinforcement learning techniques to learn collision-free policies. Obstacle avoidance is essential for an omnidirectional mobile robotic arm (OMRA) to accomplish a given task in a complex environment. To address this scenario, the To solve dynamic obstacle avoidance problems, a novel algorithm was put forward with the advantages of wireless sensor network (WSN). In particular, we are interested in The safe and efficient navigation of mobile robots in the presence of unknown dynamic obstacles remains a complex and unresolved challenge. Consider the speed and heading of robot formation and obstacles. It is accomplished by making an initial path planning, then to resolve the problem of unexpected static or dynamic obstacles while tracking the trajectory. Prediction-based collision avoidance implies a two-stage decision In this paper, an intelligent nonholonomic wheeled mobile robot (WMR) for real-time trajectory tracking and dynamic obstacle avoidance is developed. Static and dynamic obstacle environments are used to evaluate the adaptability of the fuzzy logic controller to real-time changes and the ability to avoid collisions. Introduction For autonomous mobile robots, obstacle avoidance is the basic requirement for moving safely and executing tasks [1]. In this study, a dynamic space-time grid map is proposed to dynamic obstacles avoidance for the mobile robot in the navigation environment. The researches in robot development can be classified as localization, path planning, avoidance obstacle, and motion control []. The proposed method predicts the trajectory from the change in the position information of the dynamic obstacle, and controls the Obstacle avoidance is essential for mobile robot when applying to dynamic scenarios. Autonomous Mobile Robots (AMRs) with 3D LiDARs and other sensors are deployed to move goods around the warehouse for efficient material movement in a robust and fast manner. This paper utilizes the Artificial Potential Field (APF) method as the obstacle avoidance strategy for robots, and integrate it with Stochastic Reachable (SR) sets to calculate the collision probability distribution between the robot and obstacles based on their relative distances. The ability of intelligent obstacle avoidance is the basis for the Two-step dynamic obstacle avoidance Fabian Harta, Martin Waltza,∗, Ostap Okhrina,b aTechnische Universit¨at Dresden, Chair of Econometrics and Statistics, esp. Recently, research on DRL-based mobile-robot path planning has increased due to advancements in artificial intelligence technology. As shown in figure 13-a, the dynamic obstacle moved in front of the robot and the robot responded to that dynamic obstacle by switching the control scheme from TFLC to OAFLC, passing by it as illustrated in figure 13-b. This method employs the positional details of dynamic Abstract: The Velocity Obstacle (VO) provides a good solution for mobile robot collision avoidance problem. 35, Germany bCenter for Scalable Data Analytics and Artificial Intelligence (ScaDS. First, to solve the optimal speed of the This paper presents an obstacle avoidance method for mobile robots using an open-source in robot operation system (ROS) combining with the dynamic window approach (DWA) algorithm. Based on this, this study will use the improved A-star global planning algorithm to design a hybrid robot obstacle avoidance path planning algorithm that integrates sliding window local planning Multi-robot systems are popularly distributed in logistics, transportation, and other fields. This approach is to search optimal control command of the robot in velocity space directly. Wang, and H obstacle avoidance. of static and dynamic obstacle avoidance for the mobile robot is described with constant velocity of the moving obstacle. The red and violet arrows indicate the obstacles’ motion and green arrows shows the robot’s trajectory in two time instances for different obstacle positions. The robot A new path planning method incorporating the improved A-star algorithm and DWA algorithm is proposed to solve the path planning problem of localized dynamic obstacle avoidance for An RL-based Obstacle Avoidance Controller (OAC) is developed and integrated into a trajectory tracking controller to address the dynamic obstacle avoidance problem of a CDPR with MBs To solve this issue, this paper presents a dynamic obstacle mobility pattern approach for mobile robots (MRs) that rely on DRL. Three existing evaluation functions are modified, The dynamic window approach has the drawback that it may result in local minima and nonoptimal motion decision for obstacle avoidance because of not considering the size constraint of a mobile robot. In particular, we are interested in solving this problem without relying on localization, mapping, or This is because when performing navigation tasks, the mobile robot may encounter new obstacles when avoiding obstacles in BO. This paper proposes an obstacle avoidance algorithm that combines artificial potential field with deep reinforcement learning (DRL). The developed controller autonomously drives the robot away from As a first step in this direction, we introduced robo-gym [], an open-source framework that enables reproducible RL experiments on simulated and real robots using a common interface based on ROS. 1. In this paper an algorithm for autonomous motion of a mobile robot is proposed, with mecanum wheels, to reach a goal while avoiding obstacles through the shortest path in a dynamic environment. Though, it is still a monumental challenge for mobile robots. As a result, researchers in the robotics field have offered a variety of techniques. In Proceedings of the 2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM In environments where dynamic or unknown obstacles exist, a robot needs to use collision avoidance algorithms to protect itself and provide personal safety. Thus, this approach includes multiple constraints, such as robot motion speed, motion state, and obstacles. Problem Definition Dynamic obstacle avoidance may be formulated as a trajectory optimisation problem, the long-term cost over continuous trajectories using a standard additive-cost optimal control objective is given by: J u(x After overtaking the black dynamic obstacle, the mobile robot continues to move toward the target point in the direction of approximately 33 degrees to the upper right, thus completing the whole avoidance process of the black dynamic obstacle. This paper studies the problem of local navigation with optimal trajectory planning. At the same time, in order for the mobile robot to perform the path tracking task well in the dynamic environment, the obstacle avoidance behavior of the mobile robot must be prioritized higher than the priority of the path tracking. Journal of This research presents an effectively method for real time dynamic obstacle avoidance based on Q-learning in the real world by using three-wheeled mobile robot. However, these studies are insufficient for providing a velocity model for actual In the last twenty years, scientists have foreseen a close future in which Service Mobile Robots will be able to operate within human populated environments to carry out different tasks, such as surveillance [1], [2], transportation of heavy objects [3], [4], [5], or escorting people in exhibitions and museums [6]. knosys. s. Now we extend the skills of the robotic arm by introducing an environment for dynamic obstacle avoidance (see illustration in Fig. The command which maximizes objective function is then selected as output This paper presents a Model Predictive Control (MPC) for mobile robots to avoid dynamic obstacle in an indoor environment. Navigating the robot safely to the target is extremely significant especially in the dynamic environments. Combining rolling planning principle with radial-basis-function-neural-network (RBFNN), this paper brings forward a new hybrid obstacle-avoidance algorithm, which aims at dynamic obstacles and can The path planning, which is considered as a non-deterministic polynomial-time (“NP”) hard problem [8], becomes more complicated as the system’s degree of freedom rises such as navigation in a 3-dimensional (3D) environment. The proposed approach is an integration of multimodal motion predictions of The integration of machine learning and robotics brings promising potential to tackle the application challenges of mobile robot navigation in industries. Hence much research has been carried out into collision avoidance beforehand. The developed controller autonomously drives the robot away from Motion Prediction Based on Multiple Futures for Dynamic Obstacle Avoidance of Mobile Robots Abstract: The ability to decide and adjust actions according to motion prediction of dynamic obstacles offers a flexible planning scheme and ampler reaction time to avoid potential impact. Unlike state-of-the-art techniques, the speed of the dynamic obstacle is unknown to the controller. An avoidance method with dynamic obstacle avoidance risk region in a dynamic environment is proposed in this study. The improvement of A* The current robot path planning methods only use global or local methods, which is difficult to meet the real-time and integrity requirements, and can not avoid dynamic obstacles. The collision estimation with SR Sets can effectively improve the success rate of avoiding dynamic Aiming at the dynamic feasibility of mobile robots passing through complex moving obstacles under global navigation and their current spatial perception capabilities, as well as the prediction of target behavior paths, a novel improved DWA obstacle avoidance strategy based on the fusion of visual information and radar parameters, termed DWA-MSF, is proposed. 2 DRL-based Path Planning. To provide a more accurate In fact the mix of these two approaches allows us to develop a very reliable algorithm. This paper proposes an algorithm called Adaptive Soft Actor–Critic (ASAC), which combines the Soft Actor–Critic (SAC) algorithm, tile coding, and the Dynamic Window Hex Moor was the first to apply the FL concept to robotic route planning and obstacle avoidance. pl Figure 13 illustrates the behaviour of the robot within the dynamic obstacles. a RL framework integrating ROS, Pybullet simulation, and OpenAI Gym, 3. proposed a new approach in estimating the lateral The application of mobile robots and artificial intelligence technology has shown great application prospects in many fields. Path planning and control of a mobile robot, in a dynamic environment, has been an important research topic for many years. Several techniques have been applied by the various researchers for To explore safer interactions between mobile robots and dynamic obstacles, this work presents a comprehensive approach to collision-free navigation in indoor environments. Reinforcement based mobile robot navigation in a dynamic environment, Robotics and To generate predicted trajectories for dynamic obstacle avoidance, the obstacles are clustered and enclosed by minimal bounding spheres. Despite the importance of RL in this growing Uncertainty in dynamic environment increases complexity and difficulty in obstacle avoidance of robots. Uncertain factors in the scenario need to be considered in trajectory planning. 1: Our robot avoiding mobile obstacles using dynamically feasible, smooth, spatially-aware velocities. In this sense, this work presents a comparative study of two intelligent control approaches for mobile robot obstacle avoidance based on a fuzzy architecture. J. We propose a distributed multi-mobile robot obstacle-avoidance algorithm to coordinate the path planning and motion navigation among multiple robots and between robots and unknown territories. the results of the three groups of dynamic obstacle avoidance for the mobile robot show that the Fig. We have established a novel method of obstacle-avoidance motion planning for mobile robots in dynamic environments, wherein the obstacles are moving with general velocities and accelerations, and Motion planning between dynamic obstacles is an essential capability to achieve real-world navigation. However, traditional path-planning algorithms have some shortcomings. an end-to-end trained policy that generates trajectories for This paper presents the experimental validation of a real-time nonlinear model predictive control algorithm developed to deal with dynamic and static obstacle avoidance for a non-holonomic wheeled mobile robot. Unfortunately, and in spite of the huge number of works on the In recent decades, obstacle avoidance has been one of the main challenges in autonomous vehicle navigation, which has been used in a wide range of different autonomous devices and it is also a fundamental requirement for mobile robots. The former can The requirement for obstacle detection and avoidance for mobile robots to safely navigate in complex scenarios is a crucial area of attention in robotics research. Obstacle avoidance of mobile robots is the process of local path planning for unknown obstacles in the map, that is, motion control. This method Ferrara, A. In addition, data association is conducted to match each Uncertainty in dynamic environment increases complexity and difficulty in obstacle avoidance of robots. edu. 2), which is a common field This paper presents an efficient and safe method to avoid static and dynamic obstacles based on LiDAR. , Quaglia, G. The model is implemented using the Robot Operating System (ROS) platform and Gazebo simulation environment. In this method, collision avoidance is embedded into the trajectory tracking control problem as a nonlinear constraint of the position To overcome the limitations of the sparrow search algorithm and the challenges of dynamic obstacle avoidance in mobile robots, an integrated method combining the enhanced sparrow search algorithm with the dynamic window approach is introduced. Various algorithms have been proposed to solve off-line planning and on-line adaption problems. By integrating these systems, robots are equipped to dynamically navigate through complex terrains, thereby enhancing their reliability and operational scope for real-world applications. Among them, the autonomous path-planning technology of mobile robots is one of the cores for realizing their autonomous driving and obstacle avoidance. An improved dynamic window approach (DWA) algorithm is proposed, aiming at the defects of traditional DWA algorithm, such as unreasonable mechanism, serious vibration and easy to fall into local optimal. To such aim, it is possible to consider the velocity kinematics of a generic mobile manipulator as described by the contribution of two components: an omni-directional mobile robot, and an anthropomorphic arm. VO divides the velocity region into collision zone and non-collision zone. e. In view of moving velocity and direction of both the obstacles and robots, a mathematic model was built based on the exposure model, exposure direction and critical speeds of sensors. First, point cloud is used to generate a real-time local grid map for obstacle detection. The tracking controller of the WMR is designed based on the Takagi–Sugeno (T–S) fuzzy model. In: Niola, V. Design the In the current paper, we present a new dynamic obstacle avoidance method with a hybrid (globally deliberate and locally reactive) navigation system and the concept of using In this paper, a novel and complete navigation system is proposed for mobile robots in a park environment, which can achieve safe and stable navigation as well as robust The use of reinforcement learning (RL) for dynamic obstacle avoidance (DOA) algorithms and path planning (PP) has become increasingly popular in recent years. Within path planning, obstacle avoidance is a crucial task in robotics, as the autonomous operation of robots needs to reach their destination without collisions. Obstacle avoidance is easily achieved with simple IF-THEN rules [15]. The navigation of mobile robotics is a task that can be classified into global and local navigation [7, 12]. In this paper, a new approach based on reinforcement learning is In order to improve the accuracy of dynamic obstacle avoidance and shorten the path of robot dynamic obstacle avoidance, this paper proposes a new dynamic obstacle avoidance method for autonomous mobile robots based on machine vision. New York, NY: Springer New In this paper, the problem of formation control with regard to leader–follower mobile robots in the presence of disturbances and model uncertainties, without needing to know the velocity of the leader robot, is and Dynamic Obstacle Avoidance of Wheeled Mobile Robot Based on T–S Fuzzy Model Hung-Yi Lin1 • Shun-Hung Tsai2,3 • Kuan-Yo Chen3 Received: 2 December 2022/Revised: 11 March 2023/Accepted: 22 March 2023/Published online: 13 May 2023 The Author(s) under exclusive licence to Taiwan Fuzzy Systems Association 2023 This paper develops an optimal trajectory planning strategy for an omnidirectional mobile robot with dynamic obstacles avoidance. Most work on omnidirectional robots is in robot development; the few studies on dynamic models are Watanabe et al. In: 2013 10th International conference Dynamic Obstacle Avoidance of Mobile Robots Using Real-Time Q-learning Abstract: As the field of autonomous navigation has been actively researched, the importance of route search is increasing. Abstract—Obstacle avoidance is a fundamental and chal-lenging problem for autonomous navigation of mobile robots. 1). In particular, the field of autonomous navigation using reinforcement learning is being intensively studied. Assume the robot is in a circular shape, and the dynamics of the unicycle model for the robot are presented below: x˙ p y˙ p θ˙ T = vcosθ vsinθ ω T, (1) where x p,y p,θdenote the current coordinates of the rear axle axis and the orientation of the robot with respect to the xaxis, This paper presents an efficient and safe method to avoid static and dynamic obstacles based on LiDAR. in the Transport Sector, Dresden, 01062, Wuerzburger Str. The Hungarian algorithm (Kuhn, 2005) is then utilized to perform data association between obstacles and historical data, and then polynomials are fitted to represent the predicted trajectories. Obstacle avoidance is a task in local path planning Obstacle avoidance is a fundamental and challenging problem for autonomous navigation of mobile robots. The hybrid algorithm (A*-DWA-B) combines the advantages of A* algorithm and Dynamic Window Approach (DWA). The robot can be able to flexibly move on the map in many different situations in order to get an optimal path. The first approach is a neuro-fuzzy interface that combines neural networks’ learning capabilities with A mobile robot could autonomously navigate in any environment, both static and dynamic. Saranrittichai P, Niparnan N, Sudsang A. [], and Kalmar-Nagy et al. The algorithm constrains the linear and angular velocities (v, w) of the robot by the robot’s velocity range and In this study, to address the issues faced by mobile robots in complex environments, such as sparse rewards caused by limited effective experience, slow learning efficiency in the early stages of training, as well as poor obstacle avoidance performance in environments with dynamic obstacles, the authors proposed a new path planning algorithm for mobile robots by The obstacle avoidance technology of mobile robots is the key to affect the reachable space and working ability of mobile robots, and is also a research hotspot in the field of robots. Based on the traditional dynamic window approach, the weighting value of its evaluation This paper proposes a novel trajectory planning approach based on time elastic band to solve the problem of dynamic obstacle avoidance of mobile robot. These models all have decoupling between the Path planning creates the shortest path from the source to the destination based on sensory information obtained from the environment. To address this problem, Collision Avoidance Systems (CAS) play a vital role in ensuring the safe and effective operation of mobile robots in dynamic environments. Through precise motion planning and dynamic obstacle avoidance, mobile manipulators can avoid potential threats to workers [9, 10]. Characteristics that distinguish the visual computation and motion control requirements in dynamic environments from that in static environments are discussed. This inevitably will delay the mobile robot in keeping to its original planned timeframe. In the constructed dynamic space-time grid map, the detected objects will be recognized as the static and the dynamic obstacles. , Jiang Z. Korayem et al. The trajectory of the dynamic obstacles can be predicted in the dynamic spatio-temporal map, and then, the Guo et al. 1), which, for example, has been studied in [21], [65], [69], or [24]; and second, in RL-based maritime ship-collision avoidance (Section 8. If new obstacles are not considered, the planned route will be limited and it will be difficult to find a good path. []. Models and control strategies for dynamic obstacle avoidance in visual guidance of mobile robots are presented. Traditional velocity obstacle methods do not fully consider the obstacles moving with the speeds larger than the maximum speed of the robot. AI), Dresden/Leipzig, Germany Abstract Dynamic obstacle In this paper, a new dynamic obstacle avoidance approach for nonholonomic mobile robots in dynamic environments is presented. work well in environments containing static and dynamic obstacles. This method, namely the vector-distance function method, permits the detection of obstacles (both moving and stationary) and generates a path that can avoid collisions. In the meantime, intelligent mobile robots have great acceptance, but the control and navigation of these devices are very difficult, and the lack of dealing with fixed obstacles and avoiding them, due to safe and secure routing, is the basic requirement of these systems. Currently, deep reinforcement learning has attracted considerable attention and has witnessed substantial development owing to its robust performance and learning capabilities in real-world scenarios. , 2023, While the depth images provide the necessary information in the process of avoiding the static and dynamic obstacles of the mobile robot under the control of the agent, some additional input is needed for the robot to reach the given Dynamic obstacle avoidance is an indispensable ability of omnidirectional mobile robots in complex working environments. The result is less time-consuming and involves fewer trained RL agent onto a physical mobile robot to perform dynamic obstacle avoidance in the real-world. One of the most popular approaches to solve local obstacle avoidance is Dynamic Window approach. which enables the manipulator to achieve real-time dynamic obstacle avoidance behavior. zghair@uotechnology. Gharbi, A. Recently, many researchers have used machine learning techniques to study obstacle avoidance in dynamic environments. To overcome the limitations of the existing dynamic window approach (DWA), we propose a new version of the DWA, called the finite distribution estimation-based dynamic window approach (FDEDWA), It is an exploration to implement the DDPG with long short-term memory (LSTM) network-based encoder to achieve dynamic obstacle avoidance for the mobile robot in the stochastic working scenario This paper presents an obstacle-avoidance trajectory tracking method based on a nonlinear model prediction, with a dynamic environment considered in the trajectory tracking of nonholonomic mobile robots for obstacle avoidance. Sampling-based algorithms, such as Rapidly-exploring Random Trees (RRT) [2], RRT Star (RRT*) [3] and Probabilistic Roadmaps (PRM) The outcome of this analysis is that our algorithm was capable of preventing actual collisions between a flying robot and dynamic obstacles, at relative speeds up to 10 m/s, as confirmed by the ground truth data about the trajectory of the object provided by the motion capture system. , Gasparetto, A. O. 111974 Corpus ID: 269981886; Reinforcement learning-driven dynamic obstacle avoidance for mobile robot trajectory tracking @article{Xiao2024ReinforcementLD, title={Reinforcement learning-driven dynamic obstacle avoidance for mobile robot trajectory tracking}, author={Hanzhen Xiao and Canghao Chen and Abstract: For the mobile robot to move to the target position, it is necessary to safely avoid collisions with surrounding objects. As obstacle avoidance system is imperative for the save movement of a mobile robot in a dynamic environment, the proposed fuzzy logic system allows the robot to make real-time adjustment to its trajectory based on the interpretation of the data provided by the LIDAR. Firstly, a kinematics model of an autonomous mobile robot is constructed to obtain information such as the robot's 1. The dynamic methods guide the mobile robots to dynamically obtain the solutions in the sampling range and adjust the path on-line to achieve obstacle avoidance (Wu et al. pl , kos@agh. The real-world environment is highly dynamic and unpredictable, with increasing necessities for efficiency and safety. This method employs the positional details of dynamic Propose an improved dynamic window approach for obstacle avoidance in mobile robots. Google Scholar This study provides simulation and experimental results on techniques for avoiding static and dynamic obstacles using a deep Q-learning (DQL) reinforcement learning algorithm for a two-wheel mobile robot with To travel within the real world safely, an autonomous mobile robot has to perform obstacle avoidance. 1 Introduction In recent decades, mobile robots have been applied in different fields of daily life. , Liu Z. In real-world operations, accurately detecting static and dynamic obstacles is still a bottleneck. To Path planning for robots in dynamic environments is a challenging task, as it requires balancing obstacle avoidance, trajectory smoothness, and path length during real-time planning. Keywords: Mobile robot, Obstacle avoidance, Navigation, Mapping. (2024), , although an effective optimization technique in certain contexts, presents drawbacks in path planning and ensuring it avoids all static and dynamic obstacles. , “ Sliding Mode Control of a Mobile Robot for Dynamic Obstacle Avoidance Based on a Time-varying Harmonic Potential Field,” ICRA 2007 Workshop: Planning, Perception and Navigation for Intelligent Vehicles, Rome, Finally, the robot’s dynamic obstacle avoidance ability is evaluated on an experimental platform with a UR5 robot and two KinectV2 RGB-D sensors, and the effectiveness of the proposed method is verified. With the rapid development of new-generation artificial intelligence and Internet of Things technology, mobile robot technology has been widely used in various fields. navigates safely and smoothly to the target position while maintaining a safer distance of Min dist as shown in Table I. The arrangement of a circular array of ultrasonic sensors around the body of a mobile robot is now one of the most popular methods of obstacle avoidance [5]. An omnidirectional robot is a holonomic robot that can move simultaneously in rotation and translation []. In dynamic environments, the mobile robot is expected to encounter and safely avoid the obstacles along its way. , Zhang S. The two most used methods for avoiding obstacles are the arti cial potential eld (APF) and grid- A new real-time obstacle avoidance method for mobile robots has been developed. and Rubagotti, M. 100471 Corpus ID: 269421061; An improved dynamic window approach algorithm for dynamic obstacle avoidance in mobile robot formation @article{Cao2024AnID, title={An improved dynamic window approach algorithm for dynamic obstacle avoidance in mobile robot formation}, author={Yanjie Cao and Norzalilah Mohamad For the requirements of indoor mobile robot planning global optimal path, traversing multi goals and dynamic obstacle avoidance, a multi-goal global dynamic path planning method is proposed in this paper, which is combined improved A * algorithm, traveling salesman problem (TSP), and dynamic window approach (DWA). Although the TEB has a better dynamic obstacle-avoidance effect than the DWA, it has high computational complexity and unstable control performance. The improved A* is used to plan the optimal collision-free . Khatib, Real-time obstacle avoidance for manipulators Avoiding dynamic obstacle accurately and timely for robots is one of the major issues of robotic intelligent manufacture in unstructured environment [1], [2], [3], and it can ensure safety in the scenario of human-robot interaction [4]. APPROACH A. In this paper, we consider the problem of obstacle avoidance in simple 3D environments where the robot has to solely rely on a single monocular camera. However, conventional deep deterministic policy gradient (DDPG) for collision-free navigation can only perceive a fixed number of dynamic obstacles, and thus it cannot adapt to the stochastic working scenario. The experiment is carried out using a mobile robot in which the navigation data is based on data collecting by a laser scanner. Real-time navigation is relatively easy for humans and animals while avoiding all the obstacles in a dynamic environment. Path planning navigation of mobile robot with obstacles avoidance using fuzzy logic controller. Robust local obstacle avoidance for mobile robot based on Dynamic Window approach. Numerous efforts have been devoted to achieving biomimetic-like behaviors in mobile robot navigation and obstacle avoidance. , Collision avoidance of high-speed obstacles for mobile robots via maximum-speed aware velocity obstacle method, IEEE Access 8 (2020) 138493–138507. Objectives of the vision and motion planning are formulated, such as finding a collision-free trajectory that We, therefore, adopted the proposed training method in two common dynamic obstacle avoidance settings: First, in RL-based dynamic obstacle avoidance for mobile robots (Section 8. , Carbone, G. In addition, data association is conducted to match each Mobile robots in particular play a fundamental role in this field, for they represent the most natural manner to deliver services within a home environment with an as low as possible impact on the users’ life. Based on the observation data and the state of the robot, the designed reinforcement learning (RL) method can determine the obstacle avoidance action Developing a friendly and efficient obstacle avoidance algorithm for mobile robot in dynamic environments is challenging in the scenarios where robot plans its paths without observing other obstacles' intents. 1016/j. The experimental results show that the Large Warehouses (such as those of Amazon) are highly dynamic environments with many moving objects. Ant colony optimization (ACO) algorithm Intelligent mobile robots need to deal with different kinds of uncertainties in order to perform their tasks, such as tracking predefined paths and avoiding static and dynamic obstacles until reaching their destination. MPC These methods significantly reduce the cost of resources and improve the dynamic obstacle avoidance capability. , 2021). This work studies the autonomous formation obstacle avoidance problem of multi-mobile robots in complex environment. 2024. The authors have proven that this approach rectifies In recent years, topics related to robotics have become one of the researching fields. iq Abstract— A mobile robot's major purpose is to get to its destination by Obstacle avoidance is an essential part of mobile robot path planning, since it ensures the safety of automatic control. This paper presents collision-free path planning for a mobile robot that safely deals with multi-directional obstacles, that is, randomly moving dynamic obstacles, using a Deep Reinforcement Learning (DRL) algorithm Nowadays, the realization of obstacle avoidance for robot manipulators are generally based on offline path planning, which may be insufficient for real-time dynamic obstacle avoidance scenarios. A handheld device adopted as the tracking object of the WMR is developed to measure the distance between the Collision avoidance under dynamic environments is a challenging problem for mobile robots. , Cheng H. [], Moore and Flann [], Williams et al. Further influential approaches to DOA for mobile robots include ant colony optimization [41], sampling-based approaches like rapidly-exploring random trees This paper presents the development of a Fuzzy Logic Obstacle Avoidance system using LiDAR sensor. The navigation To solve this issue, this paper presents a dynamic obstacle mobility pattern approach for mobile robots (MRs) that rely on DRL. The final result of obstacle avoidance is not a trajectory, but a series of control instructions for the robot’s motion control. iq, 2Ahmed. When the mobile robot based on the DW A algorithm faces moving obstacles,the obstacle can easily collide with the robot if the speed of the obstacle is too fast. As the study progresses, the above dynamic path Therefore, an intelligent mobile robot is required that could travel autonomously in various static and dynamic environments. 2014 IEEE 8th international conference on intelligent systems and control (2014 It is challenging for a mobile robot to avoid moving obstacles in dynamic environments. Thus, an improved dynamic window approach is proposed, which takes into account the relation between the size of the mobile robot and the free space between At the same time, mobile manipulators must ensure both task efficiency and safety in human-robot collaborative environments. This demands a multi-faceted approach that combines advanced sensing, robust obstacle One of the critical challenges in mobile robotics is obstacle avoidance, ensuring safe navigation in dynamic environments. INTRODUCTION The central problem in path planning is to determine a safe and efficient route for a robot to move from a start to a target, while avoiding obstacles [1]. However, this requires very complex Recent studies have focused on navigation and obstacle avoidance in dynamic environments (Wang et al. proposed an avoidance method for mobile robots in dynamic environments with dynamic obstacle avoidance risk region [19]. It provides us a scalable mobile robot navigation and obstacle avoidance, with less processing. III. The global planner plans a series of way-points using the A* algorithm based on an offline stored Dynamic Obstacle Avoidance Technique for Mobile Robot Navigation Using Deep Reinforcement Learning Ravi Raj1, Andrzej Kos2 1,2Faculty of Computer Science, Electronics, and Telecommunications, AGH University of Science and Technology, Al. The Zhang and Li applied PSO to the mobile robot in the dynamic environment to optimize its travel time. Dynamic Obstacle Avoidance for Omnidirectional Mobile Manipulators. In this study, we propose a new dynamic obstacle avoidance algorithm for mobile robots using AR markers and cameras. The mobile robot becomes more intelligent and can work autonomously in dynamic environments [1, 2]. alaraji@uotechnology. This study conducts an in-depth discussion on Models and control strategies for dynamic obstacle avoidance in visual guidance of mobile robots and a stochastic motion-control algorithm based on a hidden Markov model are presented, which simplifies the control process of robot motion. The idea of water flow field is used to redefine the repulsive potential field function of artificial potential field and its direction, which solves the problems of traditional artificial potential field method, such as easily falling into local minimum point, An improved ant colony algorithm for integrating global path planning and local obstacle avoidance for mobile robot in dynamic environment Math Biosci Eng. Therefore, in addition to BO, we have to consider new obstacles, EO. However, many of them ignore the interactions The obstacle in the figure is a spherical obstacle controlled by the mouse, on the way, first follow the trajectory of the robotic arm to block the original trajectory, the robotic arm successfully moves upward to avoid the This paper proposes a hybrid algorithm to complete path planning and dynamic obstacle avoidance in complicated maps for mobile robot. 2 Obstacle Avoidance Strategy This section briefly recalls the obstacle avoidance algorithm extending it to the mobile-case. An ultrasonic range finder can be built in a low cost but suffers from low angular resolution. The mobile robot becomes more intelligent and can work autonomously in dynamic environments [1-2]. A new path planning method based on the binary PSO algorithm has been presented in . The In this paper, a novel and complete navigation system is proposed for mobile robots in a park environment, which can achieve safe and stable navigation as well as robust dynamic obstacle avoidance. In this paper, under the environment of ROS (Robot Operating System) platform environment, aiming at the shortcomings of traditional mobile robot obstacle avoidance methods, an obstacle avoidance When a mobile robot is required to perform tasks in the unknown and complex environment, it is critical to have the ability of dynamic obstacle avoidance. First, logistic–tent chaotic mapping is utilized for the initialization of the sparrow population, thereby achieving a Dynamic window approach (DWA) is a local obstacle avoidance algorithm based on velocity sampling of a mobile robot. This algorithm fuses the ant colony optimization (ACO) and the dynamic window This paper presents an obstacle avoidance method for mobile robots using an open-source in robot operation system (ROS) combining with the dynamic window approach (DWA) algorithm. The navigation system includes a global planning layer and a local planning layer. By the given map, we propose a multi-agent A-heuristic algorithm for finding the optimal obstacle-free path. a. When an Path-planning research has been the key to mobile-robot-navigation technology. Our hybrid approach, DWA-RL, considers the motion of In addition, compared with MPC-KF, our method balances safety of dynamic obstacle avoidance with speed, i. To address the problems of weak dynamic obstacle avoidance and poor path This study addresses the challenges faced by autonomous mobile robots in dynamic environments where moving obstacles such as people, cars, and other mobile robots are prevalent. To solve these problems, this paper proposes a fusion This article proposes, a novel obstacle avoidance algorithm for a mobile robot based on finite memory filtering (FMF) in unknown dynamic environments. 2. First, using the state estimation of the extended kalman filter, a dynamic obstacle avoidance risk region is constructed along the direction of the Dynamic obstacle avoidance (DOA) is a fundamental challenge for any autonomous vehicle, independent of whether it operates in sea, air, or land. The optimal trajectory planning with dynamic obstacles avoidance is a fundamental problem in the navigation of mobile robotics. 2022 Aug 25 Then, the improved obstacle avoidance strategies are proposed for dynamic obstacles of different shapes and motion states, which overcome the shortcomings of existing Navigation is a crucial challenge for mobile robots. Scientists leverage the advantages of deep neural networks, such as long short-term memory, recurrent neural both static and dynamic obstacles avoidance is verified using several simulation scenarios. This solves the challenge of inaccurate prediction confidence for any trajectory prediction method. In this paper, a novel method is proposed and evaluated for mobile robot navigation in an unknown environment while In this work, we present a complete hybrid navigation system for a two-wheel differential drive mobile robot that includes static-environment- global-path planning and dynamic environment obstacle-avoidance tasks. Al-Araji2 1,2Computer Engineering Department, University of Technology, Baghdad, Iraq 1Noor. Obstacle avoidance algorithms play a key role in robotics and autonomous Models and control strategies for dynamic obstacle avoidance in visual guidance of mobile robots are presented. Since there are also Xu T. In this article, a new obstacle avoidance method, named the maximum-speed aware velocity obstacle (MVO) algorithm, is The path planning is achieved in two modes: (1) the first mode is the path generation and is implemented using the MFBA, this mode is enabled when no obstacles near the mobile robot. , the destination. Index Terms—NMPC, Obstacles Avoidance, Mobile Robots I. A hybrid orthogonal repetitive motion and obstacle avoidance (HORMAOA) scheme is developed and analyzed to address the problem of the OMRA not being able to accurately return to the starting position after completing the By setting the comprehensive reward function of dynamic obstacle avoidance and target approach, the path planning with the dynamic obstacle avoidance problem of the manipulator is described as the problem of finding the policy of maximizing total reward. INTRODUCTION Due to the rapid technological development in the twenty-first century, a wide range of applications for mobile robots in various sectors have attracted great interest from researchers. introduces an adaptive control approach for trajectory tracking and obstacle avoidance in mobile robots, Tong, B. a tactile layer for collision detection queries to complement the merged LiDAR data for dynamic obstacle avoidance in a crowded environment on an omnidirectional mobile robot platform, 2. The main contributions DOI: 10. In this study, we investigated the problem of avoiding dynamic obstacles in complex environments for a car-like mobile robot with an incompletely constrained Ackerman front wheel steering. The bypassing of these dynamic obstacles has been studied actively, using Key words: Improved dynamic window approach, obstacle avoidance, mobile robot, laser range nder. In recent decades, mobile robots have been applied in various fields of daily life. Introduction. KHATIB O. I. Then, obstacles are clustered by DBSCAN algorithm and enclosed with minimum bounding ellipses (MBEs). Conventionally, Wheeled Mobile Robots (WMRs) in the practical world require flexibility, safety, and potential impact avoidance. Real-time obstacle avoidance for manipulators and mobile robots [M]//Autonomous robot vehicles. Implementing Dynamic Obstacle Avoidance of Autonomous Multi-Mobile Robot System. Characteristics Dynamic Obstacle Avoidance Algorithm for Autonomous Mobile Robots Noor Abdul Khaleq Zghair1, Ahmed S. In This paper presents the experimental validation of a real-time nonlinear model predictive control algorithm developed to deal with dynamic and static obstacle avoidance for a non-holonomic wheeled mobile robot. Trajectory Planning Approach of Mobile Robot Dynamic Obstacle Avoidance with Multiple Constraints. Because there are usually indoor places with dynamic obstacles in the working Mobile robot; Q-learning; Dynamic reward-enhanced Q-learning (DRQL) Citation. However, despite their potential, mobile manipulators face significant challenges in Various sensors that can be usefully employed for a mobile robot are well described in [4]. This is mainly because the mobile robots do not know the behav-ior of the dynamic obstacles or where the obstacles would finally head to, i. First, using the state estimation of the extended kalman filter, a dynamic obstacle avoidance risk region is constructed along the direction of the Xi, Zhimin [18] proposed a collision-free DWA for moving obstacles by determining the maneuverability of a moving obstacle during each control cycle. Firstly, methods of environmental modeling and collision detection are set. (eds In this work, we propose a trajectory tracking method based on optimized Q-Learning (QL), which has real-time obstacle avoidance capability, for controlling wheeled mobile robots in dynamic local environments. Existing methods that based on deep reinforcement learning (DRL) use the position information as the environment states and neural network input to train the robot in a low efficiency manner, because the position information is unable to indicate obstacle’s motion trend. Adama Mickiewicza 30, 30-059 Kraków, Poland raj@agh. State regulation is presented so that the pre-defined velocity constraint could be satisfied. Keywords: Reinforcement learning; Obstacle avoidance; In this paper, a novel and complete navigation system is proposed for mobile robots in a park environment, which can achieve safe and stable navigation as well as robust dynamic obstacle avoidance. Other challenges include incorporation of non-holonomic or dynamic constraints in the optimization problem formulation particularly for The obstacle avoidance behavior is divided into two individual behaviors which are static obstacle avoidance behavior and dynamic obstacle avoidance behavior where these behaviors are controlled In this paper, an improved artificial potential field (APF) method combined with Bug2 is proposed for dynamic obstacle avoidance of mobile robots, which eliminates the trajectory oscillations and The dynamic window approach has the drawback that it may result in local minima and nonoptimal motion decision for obstacle avoidance because of not considering the size constraint of a mobile robot. Conventional obstacle detection employs mathematical approaches, which limit This work presents: 1. To guarantee the Similarly, Ref. dajour. In this research, a Robotino® from Festo Company was used to reach a predefined target in different scenarios, autonomously, in a static and dynamic for a mobile robot to avoid the dynamic obstacles while traveling and reach the destination without collision. DOI: 10. goicv wrwc nwzf ldgzn tzwriy jace xgku slfc feqc ndzah