Tag: 机器人
41 articles
AI Research #118: Embodied AI Mobile-ALOHA - Mobile + Dua...
Mobile-ALOHA: An open-source mobile manipulation solution combining mobile chassis and dual-arm collaboration. Uses whole-body teleoperation for low-cost...
AI Investigation #108: Complete Robot Model Training Proc...
Full robot training pipeline: pre-training, fine-tuning (LoRA), reinforcement learning, imitation learning, and human feedback for safe autonomous decision-making.
AI Investigation #107: RL and Robot Training Data Format ...
Data formats and development processes in robot and reinforcement learning systems, including time series trajectories, state-action pairs, offline RL data,...
AI Investigation #106: Robot Learning Data Collection Too...
Core data collection methods and application scenarios, covering over ten methods from manual entry, sensor collection, web crawlers, API calls, log collection...
AI Investigation #105: Robot Learning Data Collection - F...
Data collection is a critical step in robot learning development, covering demonstration video collection, trajectory recording, state-action pair generation, and data quality control strategies.
AI Investigation #104: From Model Training to Robot Deplo...
AI model deployment optimization guide: ONNX conversion, TensorRT/OpenVINO inference engines, quantization (FP16/INT8), and real-time robotics applications.
AI Investigation #103: Embodied AI Technology Landscape
Comprehensive overview of embodied AI tech stack: hardware (GPU, sensors, actuators), software (ROS, simulation), and algorithms (deep learning, RL, VLA models).
AI Investigation #102: Intelligent Robotic Arms, Autonomo...
Different types of robots have huge differences in structure, tasks and control methods, so AI algorithm adaptation strategies also need to be tailored.
AI Investigation #101: Modern AI Methods - VLA, RT-1, RT-...
Modern AI robot control methods are undergoing a major transition from reinforcement learning and imitation learning to multimodal agents driven by large models. The combination of Vision-Language-...
AI Investigation #100: Modern AI Methods - Reinforcement ...
Modern AI methods for robot control cover Reinforcement Learning (RL), Imitation Learning (IL), and Transformer-based large model methods. Reinforcement...
AI Investigation #99: Sensor Fusion Technology - Camera, ...
Sensor Fusion is a core technology in autonomous driving, robotics and smart security. Through multi-sensor data fusion of cameras, LiDAR, radar, IMU,...
AI Investigation #98: Visual SLAM - ORB-SLAM, RTAB-Map, V...
Visual SLAM is a technology that achieves autonomous positioning and environment mapping without relying on LiDAR, using only cameras. By extracting environmental features (corners, edges, textures...
AI Investigation #97: SLAM Algorithm Comparison and Appli...
Multi-sensor fusion and SLAM are core technologies for robot perception and navigation. By fusing IMU, GPS, wheel odometry, LiDAR, visual odometry and other...
AI Investigation #95: Robot Scenario Testing - From Extre...
Before robots enter practical applications, systematic scenario testing must be conducted, covering boundary conditions like extreme weather, complex terrain,...
AI Investigation #94: Robot Algorithm Real Machine Valida...
This article explores three core aspects of robot algorithm real machine validation - test platform selection, deployment process design and interface integration, covering mobile robot platforms l...
AI Investigation #93: Robot Simulation Tools - Comprehens...
Simulation tools are an important part of robot R&D, enabling algorithm verification and system debugging in risk-free environments, accelerating iteration.
AI Investigation #92: Robot Motion Control - From Traditi...
Robot motion control can be divided into two categories: traditional model-based methods and deep learning-based intelligent control. The former emphasizes kinematics/dynamics modeling, trajectory ...
AI Investigation #91: Multi-modal Data Annotation Tools -...
In robot vision and perception model training, high-quality multi-modal data annotation tools are crucial. Current mainstream solutions cover 2D images, video, text, audio and 3D point cloud multi-...
AI Investigation #90: Robot Data Collection and Communica...
Modern robot systems require efficient data collection and communication middleware to connect sensors, controllers and computing units, achieving collaborative perception, control and decision-mak...
AI Investigation #76: When Robots Enter Life - Embodied A...
The widespread application of embodied AI is profoundly changing social structure. Automation will replace many repetitive jobs while creating new occupations, leading to job polarization in the em...
AI Investigation #75: From LLM to LBM - Robot Hierarchica...
The integration of Large Language Models (LLM) with robot real-time control is driving intelligent upgrades in robotics. LLMs show great potential in...
AI Investigation #74: Robot Learning Breakthroughs - Meta...
This article explores fast learning capabilities of embodied AI agents, focusing on meta-learning and few-shot learning methods, as well as technical challenges and solutions for simulation-to-real...
AI Investigation #73: Embodied AI Future Trends - From Te...
In the next decade, embodied AI will undergo paradigm shifts: centered on 'pre-trained world models + online learning', software-hardware collaboration and interdisciplinary fusion accelerating, di...
AI Investigation #72: Embodied AI Development Challenges ...
Embodied AI development faces six core challenges: data scarcity, hardware limitations, training efficiency, cost bottlenecks, standardization and industrial ecosystem, safety and ethics. Only by a...
AI Investigation #71: Embodied AI Case Studies - From ROS...
Typical practices of embodied AI in architecture, capabilities and applications. In open source, ROS robot operating system has become the de facto industry...
AI Investigation #70: Embodied AI Industry Ecology and De...
Embodied AI is leading a new round of technological revolution. The market size is expected to grow from $2.53 billion in 2024 to $8.76 billion in 2033, with a CAGR of 15%.
AI Investigation #69: Embodied AI Key Capabilities - Algo...
Systematic overview of five key capability dimensions of embodied AI: intelligent algorithms, high-performance hardware, simulation and virtual environments, embedded and software systems, and data...
AI Investigation #68: Embodied AI Application Landscape -...
Systematically explore the application prospects and development trends of embodied AI in multiple fields, covering core scenarios including home, industry, healthcare, transportation and virtual i...
AI Investigation #67: Embodied AI Core Technology - Perce...
Embodied AI technology can be summarized as a 'perception-decision-control-learning-interaction' closed-loop system. The perception layer consists of various sensors, providing environment modeling...
AI Investigation #66: Robotic Arm Software Algorithm Syst...
Robotic arm software algorithm system covers core technologies including kinematics, trajectory planning, robot vision, artificial intelligence and machine learning, force control and compliance st...
AI Investigation #65: Robotic Arm Control Technology Evol...
Implementation of robotic arm systems requires software-hardware collaboration, with strict requirements from control layer to safety mechanisms. Control systems have evolved from PLC to MPC.
AI Investigation #64: Building a Robotic Arm from Scratch...
Building and controlling a high-performance robotic arm requires integrating multiple core modules including motor drive, reducer, mechanical structure, sensor system, controller and end effector.
AI Investigation #63: Full-scenario Applications of Robot...
Modern robotic arms undertake various key tasks in industrial automation: handling, assembly, welding, spraying, grinding, unstructured grasping, machining, inspection and testing.
AI Investigation #62: Five Major Robotic Arm Application ...
Robotic arms, as important tools for modern automation, have been widely applied in manufacturing, healthcare, agriculture, services and scientific research.
AI Investigation #61: Complete Industrial Robot Types Ana...
Complete industrial robot spectrum: articulated robotic arms suitable for complex trajectory tasks like automotive manufacturing; SCARA for high-speed planar...
AI Investigation #60: Robotic Arm Technology Development ...
Robotic arm technology development shows five major trends: high precision, collaboration, lightweight, intelligence, and connectivity. Industrial, service and DIY segments each have their own char...
AI Investigation #59: Robotics Career Map - Development P...
The robotics industry is experiencing rapid development, with surging demand for interdisciplinary talent with mechanical, electronic, control and software capabilities. Career path starts from ass...
AI Investigation #58: Robotics - From Factories to Homes,...
As a general-purpose technology, robots are widely used in manufacturing, healthcare, agriculture, logistics and home sectors. The industry shows three major trends: intelligence, networking, and c...
AI Investigation #57: Five Major Categories of Robots - I...
Robots can be divided into five major categories based on function and form: industrial robots, service robots, humanoid robots, mobile robots, and specialty robots.
AI Investigation #56: Robotics Technology Iteration - Evo...
Robotics has undergone profound evolution from early hydraulic drive and analog control to modern electric drive, digital control and perception systems.
AI Investigation #55: Robotics - A Century of Evolution f...
Since the term 'Robot' was first introduced in 1921, robotics has undergone a century of evolution from science fiction to reality. Starting with Unimate in 1959 pioneering the industrial robot era...