Robot navigation methods attention. As said by Blaasvaer et al. Dec 13, 2022 · Navigation is one of the most heavily studied problems in robotics, and is conventionally approached as a geometric mapping and planning problem. Both PSO and genetic algorithms exhibit low convergence speeds and medium scalability, suggesting that while they can manage a moderate number of robots, their efficiency diminishes as the A Comprehensive Review on Autonomous Navigation Apr 1, 2023 · Recent years have seen a dramatic rise in the popularity of autonomous mobile robots (AMRs) due to their practicality and potential uses in the modern… From a mobile robot control perspective, the relation between robot’s base linear and angular to angular velocity of each wheel is more valuable. However, real-world navigation presents a complex set of physical challenges that defies simple geometric abstractions. Therefore, rapidly and safely planning travel routes has become an important research direction for autonomous mobile robots. The solution combines a semantic laser SLAM system that utilizes deep learning and a trajectory interpolation algorithm. In recent years, it has become one of the key methods to achieve autonomous navigation of robots. 18 hours ago · To test how well GCL works, researchers used a dataset called the Benchmark Autonomous Robot Navigation (BARN). In this work, an autonomous robot navigation method based on reinforcement The robot only needs to continuously approach the destination during the movement and avoid obstacles around it during the progress. The paper discusses Jan 12, 2022 · A co-occurrence network of the keywords of the included papers is shown in Figure 2; the network illustrates three clusters that approximately represent topics related to human-robot interaction or social aspects of navigation (red), algorithmic methods for navigation (blue), and navigation systems (green). LLMs such as GPT-3 [11] and BERT [12] are pre-trained on vast amounts of textual data, en- Jan 1, 2024 · The aim of this paper is to offer insights into various SLAM approaches to researchers, practitioners, and developers in the field of automated guided vehicles and autonomous mobile robots, facilitating the selection of suitable SLAM methods for specific applications and fostering innovation in autonomous navigation and mapping. 15406/iratj. For each component, we have further subdivided our treatment of the subject on the basis of structured and unstructured environments. To address the safety issue in crowd-aware robot navigation with learning methods, [24] proposed safety rules by considering high-level obstacle information to make robots navigate safely. For indoor robots in structured environments, we have dealt separately with the 18 hours ago · Scenario 3: A wheeled robot transitioned between hard surfaces and softer terrains. Dec 24, 2022 · The urge to present a survey paper is twofold. Then we systematically compare and analyze A Laser SLAM Navigation Method (Simultaneous localization and mapping) for Mobile Robots (or L-SLAM AMR) uses laser sensors to scan the environment and determine the robot’s position in real-time by matching a pre-set map. At the moment, several strategies in the field of mobile robot navigation have been created by many experts, and it is the most investigated issue nowadays. , 2019), the probabilistic Hough transform Oct 2, 2024 · robot navigation methods have garnered significant. We propose a Jun 7, 2024 · This research paper presents a comprehensive study of the simultaneous localization and mapping (SLAM) algorithm for robot localization and navigation in unknown environments. Sep 19, 2024 · Raja and Pugazhenthi represented navigation and path planning of a mobile robot involves environment perception, localization and map building, path planning and motion control. LLMs such as GPT-3 [11] and BER T [12] are pre-trained on vast amoun ts of textual data, en-abling them to learn rich language May 1, 2025 · Through the careful optimization of the above steps, our method generates smooth and feasible paths in complex dynamic environments, greatly improving the navigation efficiency and safety of the robot. Then we systematically compare and analyze the Jan 15, 2025 · Path planning technology is crucial for ensuring that mobile robots can navigate safely and efficiently through complex and dynamic environments 1. edu Robot navigation using visual and sensorimotor information (2013) Robot localization denotes the robot's ability to establish its own position and orientation within the frame of reference . They used a harmonic function to avoid a local Despite considerable advancements, existing navigational strategies for Autonomous Mobile Robots (AMRs) often remain focused on specific domains: terrestrial, aerial, and aquatic. These methods are thoroughly discussed in a few groups, including visual Simultaneous Localization and When selecting the navigation method for a mobile robot project, it's crucial to prioritize the specific needs of your project over the allure of the latest technology. 18–23). The goal was to evaluate how well robots trained with GCL could navigate these tasks compared to traditional methods. Second, deep learning methods have revolutionized many fields including autonomous navigation. , from onboard LiDaR scanners) are read and overlaid with each other to incrementally create the contour of the environment Dec 28, 2024 · This formulation provides an effective method for dynamically balancing the robot’s navigation priorities, enhancing its ability to navigate complex environments with varying obstacle densities and dynamic obstacles. [39]. In this process, the robot must determine a Aug 30, 2024 · Exploring various robot navigation techniques unveils the methods that allow robots to move effectively in different environments. clemson. 1109/AHPCAI57455. 2,3 The current research method of SLAM problem is mainly by installing multi-type Nov 11, 2010 · When developing the navigation system of a mobile robot, the designer must choose the best navigation methods for the robot application. Jul 2, 2024 · Reinforcement learning continuously optimizes decision-making based on real-time feedback reward signals through continuous interaction with the environment, demonstrating strong adaptive and self-learning capabilities. Monte Carlo scheme is used to extract these points and their estimated probability by the sum of Gaussian method. 3. While global navigation works according to predefined data about the environment, local navigation uses sensory data to dynamically react and adjust the trajectory. With the goal of enhancing the autonomy in mobile robot navigation, numerous algorithms (traditional AI-based, swarm intelligence-based, self-learning-based) have been built and implemented independently, and also in blended manners. As for the local map includes mapping the barrier and the space, and Jan 1, 2024 · However, these methods are not able to fully solve all the problems associated with SARL. The robot is often tele-operated to explore an unknown environment. used hybrid wheeled-legged locomotion to improve the cost of transport while rolling on flat surfaces yet still allowing for legged navigation over obstacles like stairs. A is the number of robots, while S is the size of observation space. Two major components of the paper deal with indoor navigation and outdoor navigation. Valencia, Spain. This method of robot navigation can adapt to more complex scenarios and is more in line with real application situations, such as indoor dynamic scenes with a large number of moving objects. Navigation can be separated into global and local navigation. Using Twin Delayed Deep Deterministic Policy Gradient (TD3) neural network, a robot learns to navigate to a random g Mar 6, 2025 · Next, the robot navigation methods are explained based on the type of driving platform . In this paper, we analyze the recent advances in the field of swarm navigation, focusing mainly <p>Navigation is a fundamental problem of mobile robots, for which Deep Reinforcement Learning (DRL) has received significant attention because of its strong representation and experience learning abilities. 2022. robot navigation methods have garnered significant attention. 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. Various navigation techniques, including magnetic, laser-guided (LGV), natural navigation, and Simultaneous Localization and Mapping (SLAM), each have distinct advantages and IJRA ISSN: 2089-4856 Review of Vision-Based Robot Navigation Method (Budi Rahmani) 255 to be appropriate navigational purpose. Regarding this matter, several techniques have been explored by researchers for robot navigation path planning. These methods are thoroughly discussed in a few groups Feb 1, 2023 · Several studies have been carried out to address the shortcomings of the traditional Hough transform in agricultural robot navigation, including the Hough transform method based on passing known points (Li et al. Jan 1, 2019 · An intelligent autonomous robot is required in various applications such as space, transportation, industry, and defense. Scientists leverage the advantages of deep neural networks, such as long short-term memory, recurrent neural networks, and convolutional Oct 1, 2024 · The traditional navigation method is currently being supplemented or replaced in several experiments by DRL-based MR navigation. Jun 28, 2023 · The robot started at a random location in an unknown home and received the goal object category. SLAM is a process in which robots are equipped with sensors such as vision, laser, and odometer to construct a map while understanding the unknown environment. , 2018), the improved Hough transform method based on ridge parallel features (Lu et al. The paper first introduces some open-source laser SLAM algorithms and then elaborates in detail on the general framework of the In this paper, we present a novel hand-drawn map robot navigation architecture, HAM-Nav, which uses pre-trained vision language models (VLMs) to interpret visual and textual cues from hand-drawn maps for robot navigation in unknown Mobile Robot Navigation Using Hand-Drawn Maps: A Vision Language Model Approach Apr 24, 2024 · By augmenting a legged robot with wheels, Lee et al. Nevertheless, the problem of efficient autonomous robot Jan 1, 2023 · In this work, we present the related work of path planning methods in Section 2. a dynamic environment. Jul 9, 2019 · Ayari, E. See full list on opentextbooks. 1 Navigation. Mobile robots can also perform several tasks like material handling Dec 1, 2017 · techniques are believed to bring effective methods and i mprove the intelligence in mobile robot navigation. A A few type of the soft computing techniques include fuzzy logic s ystem, neural Dec 13, 2022 · In the end, learning-based methods for robotic navigation offer a set of features that are very difficult to obtain in any other way: they provide for navigational systems that are grounded in the real-world capabilities of the robot, make it possible to utilize raw sensory inputs, improve as more data is gathered, and can accomplish all this Apr 11, 2024 · Computer Science Seminar SeriesApril 11, 2024“Robot Navigation in Complex Indoor and Outdoor Environments”Dinesh Manocha, University of Maryland, College Par Apr 20, 2021 · Navigation is a fundamental problem of mobile robots, for which Deep Reinforcement Learning (DRL) has received significant attention because of its strong representation and experience learning abilities. Robot navigation in Aug 7, 2002 · Surveys the developments of the last 20 years in the area of vision for mobile robot navigation. , Siegwart, R. This involves both motion-planning, which includes the use of dynamical modeling to determine how the robot should move, and path-planning, which involves spatial and geometrical Jun 5, 2020 · In the early days, the emergence of simultaneous localization and mapping 1 (SLAM) technology has significant significance for mobile robot navigation. The new method performed better than traditional methods, keeping the robot stable while navigating. These techniques are central to the development of autonomous systems, facilitating seamless operations across a range of applications. 2) based on work of Fallah et al. Jan 1, 2025 · It can be seen that imitating good past experience and combining traditional method can improve the autonomous navigation ability of the robot. While moving, subsequent sensors’ scans (e. Tasks Sep 1, 2022 · The navigation procedure directs the robot to region with high uncertainty defined at representative points by characterization of likelihood. The materials and methods section is presented in Section 3, where we present the robot navigation methods and algorithms. , Hadouaj, S. Using various reinforcement learning techniques, the robot was trained to smoothly transition between walking and driving Jan 7, 2017 · Citation: Pandey A, Pandey S, Parhi DR (2017) Mobile Robot Navigation and Obstacle Avoidance Techniques: A Review. DOI: 10. Oct 23, 2022 · Successful robot navigation in unknown environments relies mostly on the surrounding information they perceive. (DOI: 10. (2013) (human navigation system), Desouza and Kak (2002) (map-based, map-building and map-less methods), Anderson et al. This paper presents a review of various state-of-the-art vision-based methods that deal with the perception problems for mobile robot navigation and control in unknown environments. In traditional path planning and navigation methods, pre-planned routes or obstacle avoidance algorithms are usually used to achieve robot navigation. , obstacles and other hazards) encountered on the way. Scenario 4: This scenario had slippery snow over concrete. Performing this task requires determining where the robot is (point A), where it needs to be (point B), how it should get to B (path in an unstructured enviroment from A to B), and how to deal with environmental factors and contingencies (e. Meanwhile, in Feb 18, 2025 · Navigation systems are developing rapidly; nevertheless, tasks are becoming more complex, significantly increasing the number of challenges for robotic systems. 2 days ago · Table 5 also illustrates the characteristics of various multi-robot navigation methods. This paper elaborates on traditional path-planning algorithms and the limitations of these algorithms in practical applications. classical methods might not be effective in real-time Sep 20, 2024 · Robot navigation methods allow mobile robots to operate in applications such as warehouses or hospitals. There is a growing trend of applying DRL to mobile robot navigation. Smooth and safe navigation of mobile robot through cluttered environment from start position to goal position with following safe path and producing optimal path length is the main aim of mobile robot navigation. For that purpose knowledge about wheel parameters is required, and the kinematic model of differ-ential drive in robot’s frame is described as follows: ⎡ ⎣ V x V y θ˙ ⎤ ⎦ = ⎡ ⎣ r 2 2 Aug 1, 2019 · Here, the robot follows the negative gradient to avoid the obstacle and reach the target point. (1994): “each navigation context imposes different requirements about the navigation strategy in respect to precision, speed and reactivity”. , & Ghedira, K. (2018a) (empirical methodology of the embodied navigation) and Yasuda et al. In this paper, we review DRL methods and DRL-based navigation frameworks. IEEE 5th International Multi-conference on Computing in the Global Information Technology (pp. , fast driving in a hospital). 10087821) Successful robot navigation in unknown environments relies mostly on the surrounding information they perceive. Robot navigation refers to the process by which a robot is able to move from its current location to a desired destination while avoiding obstacles in its path. Research in multiple robot navigation has gained more attention given their potential real-world applications, such as search and rescue, transportation, precision farming, and environmental monitoring. This method is not only suitable for static environments but also can cope with dynamic changes well, improving the overall performance of the Sep 1, 2022 · This survey divide the mobile robot navigation system into three levels: Mission, Goal Task, and Functional Component (as shown in Fig. . Cesari, G. This dataset contains various navigation tasks that robots must complete in complex environments. End-to-end learning completely replaces the classical navigation pipeline with a single neural network that takes raw sensor data as input and outputs control commands. At each step, the robot observed first-person RGB and depth images and took a discrete navigation action: move forward (25 cm), turn left or right (30°), or stop. 2 Fusion Algorithm. (2020) (statistics report of Feb 21, 2025 · Motion Control, which directs the robot's movement to travel along the intended route. Leveraging a tightly coupled perception-to-control Sep 26, 2021 · Swarm navigation is one of the possible collective behaviours a swarm robotic system can possess. Application of this method for mobile robot navigation is presented by Garibotto et al. The SLAM algorithm is a widely used approach for building a map of an environment and estimating the robot’s position within it, which is especially useful in dynamic and unstructured environments. (2010) A fuzzy logic method for autonomous robot navigation in dynamic and uncertain environment composed with complex traps. Dec 31, 2020 · Robot navigation is a process designed with the ability to avoid any hitches or obstacles while aiming at a specific predefined position. This approach, however, did not consider the time efficiency and Feb 16, 2025 · With the development of robotics technology, there is a growing demand for robots to perform path planning autonomously. Navigation is a fundamental task for agricultural robots. g. In our future work, we will adopt a decaying learning rate strategy and introduce meta -learning and transfer learning methods to further enhance the generalization capability of our model from the Aug 17, 2024 · Mobile robot navigation has been a very popular topic of practice among researchers since a while. The robot needed to take the stop action when it believed that it reached the goal Nov 8, 2024 · Navigation is a crucial challenge for mobile robots. However, these methods suffer from high pre-modelling requirements for the environment, poor adaptability and inability to cope with complex dynamic environments. The new navigation approach allowed it to maintain a smooth path while adjusting for uneven ground. Mar 26, 2025 · Navigating a nonholonomic robot in a cluttered, unknown environment requires accurate perception and precise motion control for real-time collision avoidance. Deep Reinforcement Learning for mobile robot navigation in ROS Gazebo simulator. 02. First, autonomous navigation field evolves fast so writing survey papers regularly is crucial to keep the research community well-aware of the current status of this field. A new obstacle avoidance strategy in an unknown environment is discussed by Kim et al. Int Rob Auto J 2(3): 00022. In this subsection, the A* algorithm and the improved DWA are fused and applied to path planning. Path planning is effectively an extension of localization, in that it requires the determination of the robot's current position and a position of a goal 4. 1 Robots Without Collaborative Functions Involving Humans For robots without collaborative functions involving humans, navigation driving of the robot is performed in a manner that can be removed from the generated external force, rather than using a Jul 4, 2024 · This paper proposes a solution to the problem of mobile robot navigation and trajectory interpolation in dynamic environments with large scenes. While the environment in which the robot operates imposes requirements on its navigation behavior, most existing methods do not allow the end-user to configure the robot's behavior and priorities, possibly leading to undesirable behavior (e. 5. & Dubé, R. Apr 1, 2023 · The creation of these grid maps for robot navigation is often achieved by the application of SLAM methods. This article presents neural proximal alternating-minimization network (NeuPAN): a real-time, highly accurate, map-free, easy-to-deploy, and environment-invariant robot motion planner. The results are presented in Section 4 and the conclusions in Section 5 respectively. [40] by using APF. 00023 Mobile Robot Jan 1, 2020 · PDF | On Jan 1, 2020, Florian Spiess and others published Survey and Experimental Comparison of RGB-D Indoor Robot Navigation Methods Supported by ROS and Their Expansion via Fusion with Wheel These methods attempt to address the shortcomings of classical navigation with Machine Learning at the cost of high training time, complexity, and data efficiency by training models to replace the functionality of proven low level controllers used in classical navigation techniques. Machine learning offers a promising way to go beyond geometry and conventional planning, allowing for navigational systems that Jun 1, 2024 · There are three main categories of learning methods for mobile robot navigation: end-to-end learning, subsystem replacement learning, and component adaptation learning. 2. 5. 2017. This study focuses on enhancing the most challenged task in MR’s navigation: path planning which provides a critical problem in the creation of autonomous navigation due to the robot’s kinematic and dynamic constraints. kvrd pezm blfx gjah urp pnmmhnc ptif svziu ikao yqltd