Draft:Autonomous Mobile Robot
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Submission declined on 19 June 2026 by Helpful Raccoon (talk).
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Submission declined on 6 May 2026 by EatingCarBatteries (talk). This draft duplicates another submission, Commercial cleaning robot, currently submitted for review. To save time, we will review the other submission only. Any future edits or improvements should be made on that submission, not here. Declined by EatingCarBatteries 2 months ago. | |
Submission declined on 2 May 2026 by Pythoncoder (talk). This draft appears to contain text generated by a large language model (such as ChatGPT). You cannot use LLMs to generate article content.
Declined by Pythoncoder 2 months ago.LLM-generated pages with certain obvious signs of being machine generated may be deleted without notice. These tools are prone to specific issues that violate our policies:
Instead, only summarize in your own words a range of independent, reliable, published sources that discuss the subject. See the advice page on large language models for more information. | |
Comment: Filled with vague and superficial analysis characteristic of LLM usage such as Reviews have identified challenges related to navigation in dynamic environments, robustness of perception and localization, traffic management in dense fleets, charging and scheduling, software integration with surrounding systems, and validation of safe operation around people and other equipment
(which was added after a previous LLM decline); please remove all text from the draft and start over from a blank slate without LLMs. Helpful Raccoon (talk) 03:15, 19 June 2026 (UTC)
- Comment: What is this??? "Because the AMR market changes rapidly and promotional claims are common in vendor materials, encyclopedic treatment usually relies on standards documents, review literature, and independent reporting rather than company rankings or marketing descriptions." —pythoncoder (talk | contribs) 10:05, 2 May 2026 (UTC)
An autonomous mobile robot (AMR) is a mobile robot that uses onboard sensing and control to navigate through its operating environment. In intralogistics, AMRs are used for material transport and handling in settings including manufacturing facilities, warehouses, cross-docking facilities, freight terminals, and hospitals. Academic literature commonly describes operation in changing environments and a greater degree of decentralized control as characteristics that distinguish AMRs from conventional guided-vehicle systems.[1][2]
Terminology and relationship with AGVs
[edit]The term autonomous mobile robot is frequently used in comparison with automated guided vehicle (AGV), although standards do not always treat the two expressions as mutually exclusive categories. ISO 3691-4:2023 lists both “automated guided vehicle” and “autonomous mobile robot” as examples of driverless industrial trucks.[3]
In their review of intralogistics systems, Fragapane and colleagues describe conventional AGV systems as systems in which a central unit controls scheduling, routing, and dispatching. In the same review, AMRs are described as being able to communicate with machines and other systems and to support more decentralized decision-making. This allows planning and control decisions to respond to changes in the state of the system or its environment.[1]
Lackner and colleagues make a related distinction between centrally controlled AGVs that rely on supporting infrastructure and AMRs that use onboard sensors to navigate without that form of guidance. The authors also note that changing plant layouts and dynamic manufacturing environments are factors considered in the use of AMRs for intralogistics.[2]
Navigation and control
[edit]Navigation by a mobile robot involves determining its position, selecting a route, and controlling its movement through the environment. A review by the United States National Institute of Standards and Technology discusses localization, navigation, control, path planning, and interaction with people as important subjects in the implementation of mobile robots in manufacturing.[4]
Path planning and obstacle avoidance are parts of autonomous navigation. Global path planning uses previously available information about an environment to calculate a path between a starting point and a destination. Local planning responds to obstacles and other changes encountered while the robot is moving, particularly in dynamic or partly unknown environments.[5]
Deployments involving more than one robot also require decisions about task assignment, routing, scheduling, and traffic coordination. These decisions may be made by a central management system or distributed among robots and other resources, depending on the control architecture used.[1]
Applications
[edit]Research on AMRs in intralogistics covers applications in manufacturing, warehousing, cross-docking, freight terminals, and hospitals.[1] In manufacturing, mobile robots may transport components between workstations and storage areas. They may also operate as part of systems in which several vehicles coordinate material movement within a facility.[4]
In warehouses and other intralogistics environments, AMRs are used for automated material transport and handling. Their navigation and control systems allow routes and task assignments to be changed without rebuilding a fixed physical guidepath. Research in this field examines both individual robot operation and the planning of systems containing multiple robots.[1][2]
Hospitals are also included in the intralogistics literature because internal transport tasks take place in environments shared by staff, patients, equipment, and other moving objects. Planning studies therefore consider the effect of changing surroundings on robot routing and scheduling.[1]
Safety and standards
[edit]The operation of mobile robots around people and other equipment requires consideration of both the robot and its operating area. The NIST review discusses safety in collaborative manufacturing applications, including interactions between mobile robots and people.[4]
ISO 3691-4:2023 specifies safety requirements and verification methods for driverless industrial trucks and their systems. The standard states that the condition of the operating zone has a significant effect on safe operation. It applies to powered trucks designed to operate automatically, but does not cover vehicles guided only by mechanical rails or guides, or vehicles that are operated solely by remote control.[3]
In the United States, ANSI/A3 R15.08-2:2023 addresses industrial mobile robot systems and their applications. It describes an IMR Type A as an AMR without an attachment, an IMR Type B as an AMR with a passive or active attachment other than a manipulator, and an IMR Type C as a system using an AMR or AGV platform with a manipulator.[6]
Research topics
[edit]A 2024 review of AMRs in intralogistics grouped the literature into five research subjects: environmental complexity, safety, resource scheduling and power consumption, artificial-intelligence algorithms, and interoperability. The review identified these subjects by classifying existing studies rather than by evaluating particular commercial products.[2]
Research on navigation includes comparisons of classical and heuristic methods for path planning and obstacle avoidance. Methods reviewed in the literature include graph-search algorithms, potential-field approaches, sampling-based methods, population-based optimisation, neural networks, and deep-learning methods. The suitability of a method depends on factors such as available environmental information, computational requirements, and whether obstacles are static or changing.[5]
See also
[edit]- Automated guided vehicle
- Autonomous robot
- Mobile robot
- Mobile manipulator
- Service robot
- Warehouse automation
References
[edit]- ^ a b c d e f Fragapane, Giuseppe; de Koster, René B. M.; Sgarbossa, Fabio; Strandhagen, Jan Ola (2021). "Planning and control of autonomous mobile robots for intralogistics: Literature review and research agenda". European Journal of Operational Research. 294 (2): 405–426. doi:10.1016/j.ejor.2021.01.019.
- ^ a b c d Lackner, Thorge; Hermann, Julian; Kuhn, Christian; Palm, Daniel (2024). "Review of autonomous mobile robots in intralogistics: state-of-the-art, limitations and research gaps". Procedia CIRP. 130: 930–935. doi:10.1016/j.procir.2024.10.187.
- ^ a b "ISO 3691-4:2023 — Industrial trucks — Safety requirements and verification — Part 4: Driverless industrial trucks and their systems". International Organization for Standardization. Retrieved 22 July 2026.
- ^ a b c Shneier, Michael O.; Bostelman, Roger V. (2015). Literature Review of Mobile Robots for Manufacturing (PDF) (Report). NISTIR. National Institute of Standards and Technology. doi:10.6028/NIST.IR.8022.
- ^ a b Katona, Kornél; Neamah, Husam A.; Korondi, Péter (2024). "Obstacle Avoidance and Path Planning Methods for Autonomous Navigation of Mobile Robot". Sensors. 24 (11): 3573. doi:10.3390/s24113573. PMC 11175283. PMID 38894362.
- ^ "ANSI/A3 R15.08-2-2023 — Industrial Mobile Robots — Safety Requirements — Part 2: Requirements for IMR system(s) and IMR application(s)". ANSI Webstore. American National Standards Institute. Retrieved 22 July 2026.
LLM-generated pages with certain obvious signs of being machine generated may be deleted without notice.
These tools are prone to specific issues that violate our policies:
Instead, only summarize in your own words a range of independent, reliable, published sources that discuss the subject.
See the advice page on large language models for more information.