Shenzhen PSICV Technology Co., Ltd. has officially released the “FollowMobility Autonomous Follow-Me System White Paper”, presenting a comprehensive overview of a new human-led mobility paradigm designed for logistics and industrial applications.
FollowMobility Autonomous Follow-Me System White Paper Officially Released Read More »
In the world of autonomous following vehicles, “accurate tracking” is only half of the challenge. The real test lies in ensuring the robot can follow smoothly while safely avoiding obstacles in complex environments. Behind this capability are the path planning and obstacle avoidance algorithms that form the brain of every intelligent mobile platform.
UWB provides precise positioning but suffers from signal blockage; IMU can capture rapid motion but accumulates drift over time; vision enables human and environment recognition but depends heavily on lighting and computation. As a result, the combination of UWB + IMU + Vision has become a mainstream solution in the industry. This article explores its architecture, workflow, and the key challenges faced in real-world deployments.
n recent years, the market for service robots and intelligent mobile devices has been evolving rapidly. Follow-me technology has moved beyond being a mere concept and is now powering real-world products. From autonomous luggage in airports to smart shopping carts in retail stores and assistive wheelchairs for seniors, the core capability behind all these innovations is the same: how to reliably identify and track a user while navigating in dynamic environments.
This article provides an in-depth technical explanation of TOF / TDOA / PDOA algorithms, discusses how the TOF “propagation time Δt” is derived, and presents a comparative analysis to support engineering decisions and product planning.
Principles and Application Comparison of TOF / TDOA / PDOA Algorithms Read More »
This article collects the practical algorithms (TOF / TDoA / PDoA), fusion and filtering patterns, low-power tactics, and real-world pitfalls — with pointers to the recent standards, chip docs and papers that matter today.
UWB for Follow-Me Devices: Algorithms, Power, and Practical Tips Read More »
At PSICV, we have been working on UWB-
based auto-follow solutions for several years. Through countless field tests and deployments, we have learned that security and interference resistance are not optional “extras” – they are the invisible armor that determines whether an auto-follow product can operate safely in the real world.
In autonomous following systems, Ultra-Wideband (UWB) technology, with its centimeter-level accuracy, has emerged as one of the most widely adopted localization methods. We propose a multi-sensor fusion approach, combining UWB with Inertial Measurement Units (IMU) and LiDAR. This integration significantly enhances accuracy, stability, and robustness across a wide range of real-world scenarios.
UWB-Based Autonomous Following and Multi-Sensor Fusion Localization Read More »
Ultra-Wideband (UWB) technology introduces a breakthrough in this field. With centimeter-level accuracy, sub-millisecond latency, and strong resistance to multipath interference, UWB enables robust tracking and following in both indoor and outdoor environments.
UWB-Based Autonomous Following Technology: Principles and Core Architecture Read More »
Ultra-Wideband (UWB)–based following technology leverages wide-spectrum radio signals to enable autonomous tracking of moving targets. This paper analyzes the key strengths and weaknesses of UWB following systems, identifies challenges in real-world applications, and outlines promising development directions, including sensor fusion and large-scale integration into consumer electronics.
Ultra-Wideband (UWB) Following Technology: Advantages, Challenges, and Future Directions Read More »