Piece Picking Robots Market Report Scope & Overview:

Piece Picking Robots Market was valued at USD 1.73 Billion in 2025 and is expected to reach USD 119.01 Billion by 2035, growing at a CAGR of 52.72% from 2026–2035.

The piece picking robots market is experiencing consistent growth due to increasing demand for automated, flexible, and efficient order fulfillment solutions. The expansion of e-commerce, retail distribution, warehouses, third-party logistics, grocery and FMCG operations, and pharmaceutical supply chains is driving demand for robotic piece picking. Advances in collaborative robots, fixed-arm robots, mobile piece-picking autonomous mobile robots (AMRs), machine vision, artificial intelligence, and robotic perception are improving picking accuracy, flexibility, throughput, and operational efficiency. Companies are focusing on faster item identification, precise grasping, higher payload capabilities, safer human-robot collaboration, and seamless warehouse integration. Growing demand for automated order picking, item sorting, order consolidation, and goods-to-person picking is accelerating the adoption of piece picking robots. The increasing use of lightweight robots, software-driven robotic systems, and robots-as-a-service models is further supporting market growth.

In March 2026, Geekplus launched its RoboShuttle V5 with an integrated Robot Arm Picking Station, combining autonomous mobile robots, multi-camera vision, and zero-shot learning to automate item picking and warehouse fulfillment. The system is designed to improve picking accuracy, throughput, SKU flexibility, and continuous unmanned operation across retail, pharmaceutical, FMCG, and 3PL warehouses.

Piece Picking Robots Market Trends

• Growing demand for automated order fulfillment is driving the adoption of piece picking robots across warehouses and distribution centers.

• Rising e-commerce, retail, pharmaceutical, grocery, and 3PL activities are increasing demand for faster and more accurate robotic picking solutions.

• Increasing adoption of collaborative robots, fixed-arm robots, mobile piece-picking AMRs, machine vision, and AI is improving picking accuracy, flexibility, and efficiency.

• Growing focus on reducing labor dependency, improving throughput, optimizing warehouse operations, and minimizing picking errors is creating opportunities for piece picking robot providers.

• Advancements in robotic vision, AI, gripper technology, autonomous navigation, and warehouse automation software are improving picking performance and supporting the adoption of piece picking robots.

The U.S. Piece Picking Robots Market Outlook

The U.S. Piece Picking Robots Market was valued at USD 0.46 Billion in 2025 and is expected to reach around USD 24.95 Billion by 2035, growing at a CAGR of 48.46% from 2026–2035.

The U.S. piece picking robots market is growing steadily due to rising demand for automated, accurate, and flexible order fulfillment solutions. The expansion of e-commerce, retail, pharmaceutical, grocery, FMCG, and third-party logistics operations is driving demand for robotic picking systems. Increasing investments in warehouse automation and smart fulfillment centers are improving operational efficiency, picking accuracy, throughput, and scalability. Growing adoption of collaborative robots, fixed-arm robots, mobile piece-picking AMRs, machine vision, and artificial intelligence is supporting automated item handling across U.S. warehouses and distribution centers. Companies are focusing on robotic vision, advanced grippers, autonomous navigation, AI-powered item recognition, and warehouse management system integration to enhance picking efficiency and flexibility. The adoption of automated order picking, item sorting, order consolidation, and goods-to-person picking solutions is further supporting market growth in the U.S.

In March 2025, Vention unveiled an AI-powered bin-picking system at NVIDIA GTC in San Jose, California, integrating robotic vision, grippers, and AI-based control to enable robots to autonomously identify, select, pick, and organize parts. The development is expected to support greater adoption of automated piece picking in U.S. warehouses and manufacturing environments by reducing programming complexity and improving picking flexibility.

Piece Picking Robots Market Segment Analysis

• By Robot Type, collaborative robots dominated the piece picking robots market with a 45.43% share in 2025, while mobile piece-picking AMRs are projected to be the fastest-growing segment, registering a 60.07% CAGR during 2026–2035.

• By Component, hardware dominated the piece picking robots market with a 57.13% share in 2025, while software is projected to be the fastest-growing segment, registering a 57.93% CAGR during 2026–2035.

• By Payload Capacity, up to 5 kg dominated the piece picking robots market with a 48.67% share in 2025, while up to 5 kg is projected to be the fastest-growing segment, registering a 54.60% CAGR during 2026–2035.

• By Application, order picking dominated the piece picking robots market with a 34.27% share in 2025, while goods-to-person picking is projected to be the fastest-growing segment, registering a 58.45% CAGR during the forecast period.

• By End User, e-commerce & retail dominated the piece picking robots market with a 53.27% share in 2025, while grocery & FMCG is projected to be the fastest-growing segment, registering a 56.40% CAGR during 2026–2035.

By Component, hardware dominated the piece picking robots market, while software is expected to grow fastest.

Hardware held the leading position in the piece picking robots market in 2025, supported by the essential role of robotic arms, grippers, sensors, cameras, controllers, and other physical components in automated picking operations. Growing adoption of collaborative robots, fixed-arm robots, and mobile piece-picking AMRs across warehouses and distribution centers is driving demand for advanced robotic hardware. Increasing requirements for higher picking accuracy, faster throughput, flexible item handling, and improved robotic perception are further supporting hardware deployment. The integration of machine vision, advanced grippers, sensors, and robotic control systems is strengthening the capabilities of piece picking robots.

Software is anticipated to register the highest CAGR during the forecast period from 2026 to 2035. Increasing adoption of AI-powered vision, machine learning, robotic perception, item recognition, motion planning, fleet management, and warehouse management system integration is accelerating demand for advanced software solutions. Growing requirements for autonomous picking, real-time decision-making, adaptive grasping, and optimized warehouse workflows are expected to further support software adoption across piece picking operations.

By Application, order picking dominated the piece picking robots market, while goods-to-person picking is expected to grow fastest.

Order picking accounted for the dominant share of the piece picking robots market in 2025, driven by increasing demand for automated item retrieval, higher warehouse throughput, improved picking accuracy, and reduced manual labor requirements. The expansion of e-commerce, retail fulfillment, pharmaceutical, grocery, FMCG, and third-party logistics operations is increasing the need for efficient automated picking solutions. The growing adoption of robotic vision, AI-based item identification, advanced grippers, and collaborative picking systems is further supporting the use of piece picking robots for order fulfillment.

Goods-to-person picking is projected to exhibit the highest growth rate during 2026–2035. The rapid expansion of e-commerce fulfillment centers, automated warehouses, and high-volume distribution operations is creating strong demand for systems that efficiently bring items to robotic or human picking stations. Increasing integration of mobile piece-picking AMRs, automated storage and retrieval systems, warehouse management software, and robotic picking stations is improving throughput, flexibility, and order fulfillment efficiency, supporting greater adoption of goods-to-person picking solutions.

By End User, e-commerce & retail dominated the piece picking robots market, while grocery & FMCG is expected to grow fastest.

E-commerce & retail held the dominant position in the piece picking robots market in 2025, supported by the rapid expansion of online shopping, fulfillment centers, automated warehouses, and omnichannel distribution networks. Rising order volumes, shorter delivery expectations, SKU proliferation, and increasing requirements for accurate and efficient fulfillment are driving retailers and e-commerce companies to adopt piece picking robots. The deployment of collaborative robots, mobile piece-picking AMRs, machine vision, and AI-based picking systems is further supporting automation across retail fulfillment operations.

Grocery & FMCG is expected to register the highest CAGR during the forecast period from 2026 to 2035. Increasing demand for automated handling of high-SKU-volume products, frequent order fulfillment, faster warehouse operations, and improved picking accuracy is encouraging grocery and FMCG companies to adopt robotic picking solutions. Growing investments in automated fulfillment centers, goods-to-person systems, mobile AMRs, robotic vision, and AI-enabled picking technologies are expected to further accelerate adoption across grocery and FMCG distribution operations.

Regional Analysis

North America piece picking robots market insights

North America accounted for a 32.46% share of the piece picking robots market in 2025, supported by the region's advanced warehouse automation infrastructure, strong e-commerce ecosystem, and widespread adoption of robotics across fulfillment centers and distribution facilities. The expansion of e-commerce, retail, pharmaceutical, grocery, FMCG, and third-party logistics operations is increasing demand for automated order fulfillment and robotic piece picking. Growing investments in warehouse automation, artificial intelligence, machine vision, autonomous mobile robots, and collaborative robots are improving picking accuracy, throughput, and operational flexibility. The presence of major technology providers and logistics companies, along with increasing adoption of smart warehouses, is further supporting regional market development.

Europe piece picking robots market insights

The piece picking robots market in Europe is expected to witness steady growth over the forecast period, supported by the expansion of automated warehouses, e-commerce fulfillment operations, logistics networks, and advanced manufacturing facilities. Increasing labor costs, workforce availability challenges, and growing demand for accurate and efficient order fulfillment are encouraging companies to adopt robotic picking solutions. The increasing deployment of collaborative robots, mobile piece-picking AMRs, machine vision, artificial intelligence, and warehouse management software is further supporting automation across European fulfillment and distribution operations.

Asia Pacific piece picking robots market insights

Asia Pacific is expected to record the fastest growth in the piece picking robots market, registering a 49.32% CAGR during 2026–2035, driven by rapid e-commerce expansion, increasing warehouse automation, manufacturing growth, and rising investments in logistics infrastructure. Countries including China, Japan, South Korea, India, Singapore, and other Southeast Asian economies are increasingly deploying automated fulfillment centers and smart warehouses to manage growing order volumes and improve operational efficiency. The expansion of e-commerce, retail, grocery, FMCG, pharmaceutical, and third-party logistics activities is creating substantial demand for automated piece picking solutions.

Middle East & Africa and Latin America piece picking robots market insights

The piece picking robots market in the Middle East & Africa and Latin America is expected to witness consistent growth from 2026 to 2035, supported by expanding e-commerce, logistics infrastructure, warehouse development, and increasing adoption of automation technologies. Growing demand for faster order fulfillment, improved inventory handling, reduced manual labor dependency, and higher warehouse productivity is encouraging businesses to invest in robotic picking solutions. Increasing development of distribution centers, retail fulfillment facilities, and third-party logistics operations is further creating opportunities for collaborative robots, mobile piece-picking AMRs, machine vision, and AI-enabled picking systems.

In Latin America, Brazil is anticipated to remain a key country-level market due to its large retail and e-commerce sector, expanding logistics infrastructure, and increasing demand for warehouse automation. Other Latin American countries are also expected to contribute to regional growth through investments in e-commerce fulfillment, distribution centers, logistics modernization, and automated warehouse technologies.

Market Dynamics

Growth Driver: Increasing demand for automated and efficient order fulfillment is driving market growth

One of the key factors driving the growth of the global piece picking robots market is the increasing demand for automated, accurate, and efficient order fulfillment across warehouses and distribution centers. The rapid expansion of e-commerce, retail, grocery, FMCG, pharmaceutical, and third-party logistics operations is generating higher order volumes and increasing the need for faster picking and fulfillment processes. As businesses face rising labour costs, workforce availability challenges, and growing customer expectations for rapid delivery, they are increasingly adopting robotic solutions to improve warehouse productivity and reduce manual handling requirements. In addition, advancements in collaborative robots, fixed-arm robots, mobile piece-picking AMRs, machine vision, artificial intelligence, robotic perception, and advanced gripper technologies are improving the accuracy, flexibility, and efficiency of automated picking operations.

Restraint: High deployment costs and technological complexity can limit market adoption

The high initial cost and technical complexity associated with deploying piece picking robots can restrict market adoption, particularly among small and medium-sized enterprises. Robotic arms, mobile AMRs, machine vision systems, sensors, grippers, controllers, software, and supporting warehouse infrastructure require significant investment. Integrating robotic picking systems with existing warehouse management systems, inventory platforms, conveyor systems, and automated storage solutions may also increase implementation costs and operational complexity.

Opportunity: Rapid expansion of e-commerce and smart warehouses creates new market opportunities

The rapid expansion of e-commerce and smart warehouse infrastructure presents significant opportunities for piece picking robot providers. Increasing order volumes, SKU proliferation, shorter delivery expectations, and growing demand for flexible fulfillment are encouraging retailers, e-commerce companies, and logistics providers to automate item handling and picking processes. The increasing development of highly automated fulfillment centers is creating demand for robotic systems capable of operating continuously while improving picking accuracy and throughput. Furthermore, the growing adoption of mobile piece-picking AMRs, collaborative robots, AI-powered vision systems, advanced robotic grippers, and goods-to-person picking solutions creates opportunities for technology providers.

Recent Developments

• 2026: RightHand Robotics continued advancing AI-powered robotic piece-picking solutions, focusing on robotic vision, intelligent grasping, item recognition, and automated picking for e-commerce and warehouse fulfillment operations.

• 2026: Berkshire Grey continued expanding AI-enabled robotic picking and sorting solutions, supporting automated item handling, order fulfillment, and warehouse operations across e-commerce, retail, and logistics applications.

• 2026: Covariant continued developing AI-powered robotic picking technologies designed to improve item recognition, grasping, and autonomous handling of diverse products across warehouse and fulfillment environments.

• 2026: Plus One Robotics continued advancing vision-guided robotic picking solutions, integrating artificial intelligence, robotic perception, and automated handling capabilities to improve picking accuracy and warehouse efficiency.

• 2026: Locus Robotics continued expanding autonomous mobile robot solutions for warehouse automation, supporting order fulfillment, material movement, and increasingly automated picking workflows across distribution and logistics facilities.

Piece Picking Robots Market key players are:

• RightHand Robotics Inc.

• Berkshire Grey Inc.

• Covariant

• Plus One Robotics Inc.

• Universal Robots A/S

• Locus Robotics Corp.

• Ocado Group plc

• KNAPP AG

• Dematic (KION Group AG)

• Swisslog Holding AG

• GreyOrange

• Mujin Inc.

• XYZ Robotics Inc.

• Nomagic Inc.

• OSARO Inc.

• Nimble Robotics Inc.

• Lyro Robotics Pty Ltd

• Robomotive BV

• Hand Plus Robotics Pte. Ltd.

• SSI SCHAEFER Group.

Piece Picking Robots Market Report Scope: