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Report ID: AD0014
Pages: 183
Base Year: 2023
Format: PDF
Historical Date: 2019-2022
MARKET SCOPE:
The global Autonomous Ship and Ocean Surface Robot market is projected to grow significantly, registering a CAGR of 27.1% during the forecast period (2024 – 2032).
An autonomous ship refers to a waterborne vessel equipped with advanced technologies, sensors, and artificial intelligence systems that enable it to operate and navigate without direct human intervention. These vessels are designed to perform various maritime tasks, such as navigation, collision avoidance, route planning, and even cargo handling, with a high degree of autonomy. An ocean surface robot is an unmanned, autonomous vehicle designed to operate on the surface of the ocean. These robots are equipped with sensors, communication systems, and often renewable energy sources. They are used for various purposes, including environmental monitoring, data collection, surveillance, and research in marine and coastal areas. An ocean surface robot is an unmanned, autonomous vehicle designed to operate on the surface of the ocean. These robots are equipped with sensors, communication systems, and often renewable energy sources. They are used for various purposes, including environmental monitoring, data collection, surveillance, and research in marine and coastal areas. The maritime industry places a high value on safety. The demand for autonomous ships is driven by the potential to reduce the risk of human error, collisions, and accidents, leading to enhanced safety in maritime activities.
MARKET OVERVIEW:
Driver: Increasing technological advancements is driving the market growth.
Ongoing advancements in sensor technologies, including radar, lidar, sonar, and other detection systems. Enhanced sensor capabilities provide autonomous vessels with improved perception of their surroundings. This includes better object detection, recognition, and tracking, contributing to safer and more reliable maritime operations. Continuous development and refinement of AI algorithms, machine learning models, and decision-making systems. Technological progress in AI enables autonomous vessels to process complex data sets, adapt to dynamic environments, and make real-time decisions. AI-driven systems enhance the autonomy and intelligence of maritime operations. Autonomous vessels leverage machine learning to analyze historical data, adapt to changing conditions, and optimize navigation routes. This results in more fuel-efficient and time-saving maritime journeys.
Opportunities: Growing need for safety and operational efficiency is anticipated for the market growth in the upcoming years.
The primary driver behind integrating autonomous systems in maritime activities is the desire to enhance safety by minimizing the risk of human error. Autonomous vessels, equipped with advanced sensors and navigation systems, can operate with precision and adherence to safety protocols, reducing the likelihood of accidents, collisions, and other maritime incidents. By automating routine tasks and decision-making processes, autonomous systems help eliminate or reduce errors caused by fatigue, distraction, or lapses in judgment, contributing to overall maritime safety. Improved awareness of the vessel’s surroundings enables better decision-making, particularly in complex maritime environments, adverse weather conditions, or congested waterways, enhancing overall safety. Autonomous vessels can operate 24/7 without the constraints of crew fatigue. This not only optimizes efficiency but also contributes to safety by ensuring vessels are constantly monitored and responsive to changing conditions.
COVID IMPACT:
The pandemic has disrupted global supply chains, affecting the production and delivery of various technologies, including those used in autonomous systems. Delays in the availability of components and equipment could impact the timelines of autonomous vessel projects. The pandemic has accelerated the adoption of remote technologies and automation across industries. In the maritime sector, there may be an increased emphasis on autonomous technologies to minimize the need for onboard crew and enhance operational resilience during health crises. The need for remote monitoring and management capabilities, which are inherent in autonomous systems, has gained importance during the pandemic. These capabilities align with the broader trend of reducing human presence on vessels to enhance safety during infectious disease outbreaks. Economic uncertainties resulting from the pandemic have led industries to focus on efficiency and cost reduction. Autonomous technologies, by optimizing operations and reducing labor costs, may become more attractive to companies seeking ways to streamline their maritime activities.
SEGMENTATION ANALYSIS:
Partial Autonomy segment is anticipated to grow significantly during the forecast period
“Partial autonomy” in the context of autonomous ships and ocean surface robots refers to a level of automation where certain tasks or functions of the vessel are automated, but human intervention or control is still required for other aspects of operation. It represents a transitional stage between fully manual operation and full autonomy. Partially autonomous vessels have certain functions or tasks that are automated. These can include navigation, collision avoidance, route planning, or specific operational tasks. Human intervention and oversight are still essential in a partially autonomous system. While some operations are automated, a human operator or crew is responsible for monitoring, decision-making, and handling situations that fall outside the scope of automation. Partial autonomy often involves the use of semi-autonomous systems. These systems can operate independently for specific functions but may require human input for complex or unexpected scenarios. Partially autonomous vessels may feature adaptive capabilities, allowing them to adjust to changing environmental conditions, traffic patterns, or unforeseen obstacles. However, the ability to adapt might be limited compared to fully autonomous systems.
Line Fit segment is anticipated to grow significantly during the forecast period
Autonomous technologies are designed and integrated into the vessel from the beginning of the manufacturing process. This integration ensures that the autonomous features are seamlessly incorporated into the overall design and structure of the ship or ocean surface robot. Line fit solutions offer a more efficient and seamless implementation of autonomous capabilities. The technology is part of the vessel’s core features, optimizing its performance and reducing the need for additional modifications. Autonomous systems that are line fit can be optimized for the specific characteristics and requirements of the vessel. This results in better performance, reliability, and safety compared to retrofitted solutions. Line fit solutions can potentially reduce the costs associated with retrofitting vessels with autonomous capabilities at a later stage. Retrofitting often involves additional expenses and modifications to existing structures.
REGIONAL ANALYSIS:
The Asia Pacific region is set to witness significant growth during the forecast period.
The concept of autonomous ships and ocean surface robots, often referred to as Autonomous Surface Vehicles (ASVs) or Unmanned Surface Vehicles (USVs), has been gaining attention globally. These are vessels designed to operate on the ocean’s surface without direct human intervention, employing various technologies for navigation, communication, and data collection. The Asia Pacific region, being a significant player in maritime activities, is likely to be involved in the development and deployment of such autonomous systems. Autonomous surface vehicles can contribute to maritime security by patrolling and monitoring coastal areas, ports, and shipping lanes. The Asia Pacific region, with its extensive coastlines and strategic maritime locations, may have a growing demand for such systems. The Asia Pacific is prone to various environmental challenges, including typhoons, tsunamis, and pollution. Autonomous surface robots can be deployed for environmental monitoring, collecting data on water quality, climate conditions, and pollution levels. Autonomous vessels can be utilized for fisheries management and aquaculture operations. These robots can assist in monitoring fish stocks, tracking migration patterns, and supporting sustainable practices in the region’s fisheries industry.
COMPETITIVE ANALYSIS
The global Autonomous Ship and Ocean Surface Robot market is reasonably competitive with mergers, acquisitions, and Autonomy launches. See some of the major key players in the market.
In 2022, A contract of USD 972 million was given to Raytheon Missiles & Defense in September 2022 to supply AMRAAMs to the US Air Force, US Navy, and 19 other countries’ militaries, including the UK, Australia, Italy, Saudi Arabia, and Japan. This contract, according to Raytheon, is the first to be made up entirely of AIM-120D3 and AIM-120C8 AMRAAMs with the most recent form, fit, and function (F3R) upgrades. These upgrades include upgraded software that will increase the missiles’ ability to counter advanced threats, as well as better circuit cards and other hardware in the AMRAAM’s guidance section.
In 2023, The Swedish Defence Materiel Administration has given Saab AB a contract to support the Swedish Armed Forces’ Ground-Based Air Defence (GBAD) systems going forward. The deal, which has options for three more years, is estimated to be worth SEK 170 million and will run from 2023 to 2025.
Scope of the Report
** In – depth qualitative analysis will be provided in the final report subject to market
Primary and Secondary Research
In order to understand the market in detail we conduct primary and secondary research. We collect as much information as we can from the market experts through primary research. We contact the experts from both demand and supply side and conduct interviews to understand the actual market scenario. In secondary research, we study and gather the data from various secondary sources such as company annual reports, press releases, whitepapers, paid databases, journals, and many other online sources. With the help of the primary interviews, we validate the data collected from secondary sources and get a deep understanding on the subject matter. Post this our team uses statistical tools to analyses the data to arrive at a conclusion and draft it in presentable manner.
Market Size Estimations
Understanding and presenting the data collected is a crucial task. Market sizing is a critical part of the data analysis and this task is performed by using Top-down and bottom-up approaches. In this process, we place different data points, market information and industry trends at a suitable space. This placement helps us presume the estimated & forecast values for coming few years. We use several mathematical and statistical models to estimate the market sizes of different countries and segments. Each of this is further added up to outline the total market. These approaches are individually done on regional/country and segment level.
Data Triangulation
As we arrive at the total market sizes, the market is again broken down into segments and subsegments. This process is called as data triangulation and is implementable wherever applicable. This step not only helps us conclude the overall market engineering process, but also gives an assurance on accuracy of the data generated. The data is triangulated based on studying the market trends, various growth factors, and aspects of both demand and supply side.