The "Swarm Intelligence and Robotic Collaboration Application Report, 2025" report has been added to ResearchAndMarkets.com's offering.

The "Swarm Intelligence and Robotic Collaboration Application Report 2025" analyzes and summarizes the definition, characteristics, core algorithms, core value, development history, technical architecture and key technologies, technology trends, challenges, key industry applications (including include intelligent warehousing and logistics, performing arts and entertainment, industrial manufacturing, consumer services, fire and rescue, etc.) and suppliers of swarm intelligence technology and robot collaborative applications.

Swarm intelligence and robotic collaboration can break through the boundaries of individual capabilities.

Compared to individual intelligence, swarm intelligence and robotic collaboration can improve efficiency, expand boundaries, enhance system fault tolerance, and reduce costs and energy consumption.

Stand-alone intelligence focuses on "enhancing individual capabilities". All perception, decision-making and actuation modules are integrated on a single robot, which independently handles problems by relying on its own sensors (cameras, radar) and algorithms, without relying on external devices or other robots. The core of swarm intelligence and robotic collaboration is "optimizing group efficiency," where multiple robots are connected through a communication network and work together to complete tasks that a single robot cannot accomplish. Each robot may only be responsible for a part of the work, achieving a "1+1>2" synergy through data sharing and task allocation.

Key technologies for swarm intelligence and robotic collaboration: task allocation, collaborative control, and real-time communication

Compared to individual intelligence, the key technologies of swarm intelligence and robotic collaboration mainly revolve around "how to enable multiple individuals to form an efficient and orderly whole." The core is to handle three major challenges: task division, behavior coordination, and information sharing.

Swarm intelligence and collaborative robot application: will be widely adopted across all industries

The application of swarm intelligence and robotic collaboration spans various industries, including warehousing and logistics, entertainment, industrial manufacturing, commercial consumer services, fire and rescue, security inspection, agriculture, and healthcare. Examples include intelligent sorting and warehousing in warehousing and logistics, drone art, robot stage performances, collaborative assembly in manufacturing, collaborative food delivery in large restaurants/hotels, and air-ground collaborative rescue.

Currently, the application of swarm intelligence and robotic collaboration in the field of intelligent warehousing and logistics is relatively mature, covering cargo loading/unloading/handling, cargo classification/sorting, collaborative handling of large items, stacking and warehousing, cross-warehouse scheduling, flexible production lines, and last-mile delivery. For example, the HaiQ Intelligent Warehouse Management Software Platform of Hai Robotics realizes "goods-to-person" picking through a variety of equipment such as bin robots, lurking autonomous mobile robots (AMRs), and intelligent forklift robots, and completes collaborative operations such as inbound and outbound, inventory, sorting, and handling.

The application of swarm intelligence and robotic collaboration in the field of drone art is maturing, with China leading the world in this field and repeatedly breaking Guinness World Records in terms of an increasing number of and scale of performances.

The application of swarm intelligence and robotic collaboration has shifted from "single-mode robotic collaboration" to "multimodal robotic collaboration" and from "structured scenarios" to "complex dynamic scenarios". In the future, with the support of 5G/6G communications, digital twins, brain-inspired computing and other technologies, swarm intelligence and robotic collaboration will empower all walks of life and facilitate deeper and larger-scale application. Unmanned factories, unmanned restaurants, and unmanned farms are coming soon, promoting changes in social production and lifestyles.

Overview of Swarm Intelligence and Robotic Collaboration

Introduction

• Swarm Intelligence Technology Originates from the Simulation of Biological Group Behavior
• Algorithms of Swarm Intelligence Technology
• Genetic Algorithms and Swarm Intelligence are Combined to Solve Complex Collaborative Problems
• Core Characteristics of Swarm Intelligence Technology
• Swarm Intelligence Is the "Brain" of Robot Collaboration
• The Core Value of Robotic Collaboration Lies in Higher Operational Efficiency and Wider Operational Boundaries
• Essential Difference between Robotic Collaboration and Standalone Intelligence: Breaking through the Boundaries of Individual Capabilities through Collaboration
• Development History of Robot Collaboration

Key Technologies for Swarm Intelligence and Robotic Collaboration

• Technology Architecture
• Key Technology: Task Allocation
• Key Technologies: Path Planning and Obstacle Avoidance
• Key Technology: Cooperative Control
• Key Technology: Communication
• System Software Architecture

Trends in Swarm Intelligence and Robot Collaboration Technologies

• In-depth Application of Edge Computing
• Fusion of Foundation Models
• Cross-modal Collaboration
• Deepened Human-Machine Integration

Development Challenges for Swarm Intelligence and Robotic Collaboration

• Hardware
• Challenge: Technology
• Challenge: Practical Application and Deployment
• Challenge: Talents
• Challenge: Security
• Challenge: Ethics and Attribution of Responsibility
• Challenge: Policies and Standards
• Standardization and Platformization Process of Swarm Intelligence and Robotic Collaboration

Key Topics Covered:

Chapter 1 Overview of Swarm Intelligence and Robotic Collaboration

1.1 Introduction to Swarm Intelligence and Robotic Collaboration

1.2 Key Technologies for Swarm Intelligence and Robotic Collaboration

1.3 Trends in Swarm Intelligence and Robot Collaboration Technologies

1.4 Development Challenges for Swarm Intelligence and Robotic Collaboration

1.5 Application Fields of Swarm Intelligence and Robotic Collaboration

Chapter 2 Application and Suppliers of Swarm Intelligence and Robotic Collaboration in Warehousing and Logistics

2.1 Application of Multi-robot Collaboration Based on Swarm Intelligence in Warehousing and Logistics

2.2 Supplier - Geek+

2.3 Supplier - Quicktron

2.4 Supplier - Hai Robotics

2.5 Supplier - IPLUSMOBOT

2.6 Supplier - Megvii

2.7 Supplier - KSEC Intelligent Technology

2.8 Supplier - Mooe Robot

Chapter 3 Application and Suppliers of Swarm Intelligence and Robotic Collaboration in Entertainment Performances

3.1 Application of Swarm Intelligence and Robotic Collaboration in Drone Art

3.2 Application of Swarm Intelligence and Robotic Collaboration in Stage Performance

3.3 Supplier - Highgreat Technology

3.4 Supplier - DAMODA

3.5 Supplier - CroStars

3.6 Supplier - EFY Technology

3.7 Supplier - EHang

Chapter 4 Application Cases of Swarm Intelligence and Robotic Collaboration in Other Fields

4.1 Application of Swarm Intelligence and Robotic Collaboration in Industrial Manufacturing

4.2 Industrial Manufacturing Supplier - UBTECH

4.3 Applications of Swarm Intelligence and Robotic Collaboration in Consumer Services

4.4 Consumer Services Supplier - Yunji Technology

4.5 Consumer Services Supplier - Gausium

4.6 Consumer Services Supplier - Keenon

4.7 Consumer Services Supplier - Pudu Robotics

4.8 Consumer Services Supplier - Excelland Robotics

4.9 Application of Swarm Intelligence and Robotic Collaboration in Fire and Rescue

4.10 Application of Swarm Intelligence and Robotic Collaboration in Facility Inspection

4.11 Application of Swarm Intelligence and Robotic Collaboration in Agriculture

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