Visual impairment or even loss seriously affects quality of life. Benefited by the rapid development of sound/laser detection, Global Positioning System (GPS)/Beidou positioning, machine vision and other technologies, the quality of life of blind people is expected to be improved through visual substitution technology. The existing visual substitution devices still have limitations in terms of safety, robustness, and ease of operation. The remote companion system developed here fully utilizes multimodal navigation and remote communication technologies, and the positioning and interaction functions of commercial mobile phones. Together with the accumulated judgment of backend personnel, it can provide real-time, safe, and reliable navigation services for blind people, helping them complete daily activities such as independent travel, circulation, and shopping. The practical results show that the system not only has strong operability and is easy to use, but also can provide users with a strong sense of security and companionship, making it suitable for promotion. In the future, this system can also be promoted for other vulnerable groups such as the elderly.

Remote Sighted Assistance (RSA) systems provide visually impaired people (VIPs) with real-time guidance by connecting them with remote sighted agents to facilitate daily travel. However, unfamiliar environments often complicate decision-making for agents and can induce anxiety in VIPs, thereby reducing the effectiveness of the assistance provided. To address this challenge, this paper proposes a video-based map assistance method. By pre-recording pedestrian path videos and aligning them with geographic locations, the system enables route preview and enhances navigation guidance. This study introduces a factor graph optimization (FGO) algorithm that integrates Global Navigation Satellite System (GNSS) and pedestrian dead reckoning (PDR) data for pedestrian positioning. It incorporates road-anchor constraints, a turning-point-based anchor-matching method, and a coarse-to-fine optimization strategy to improve the positioning accuracy. GNSS provides global reference positions, PDR offers precise relative motion constraints through accurate heading estimation, and anchor factors further enhance localization accuracy by leveraging known geometric features. We collected data using a smartphone equipped with a four-camera module and conducted tests in representative urban environments. Experimental results demonstrate that the proposed anchor-aided FGO-GNSS/PDR algorithm achieves robust and accurate positioning, effectively supporting video-based map construction in complex urban settings. With anchor constraints, the mean horizontal positioning error was reduced by 42% to 65% and the maximum error by 38% to 76% across all datasets. In this study, the mean horizontal positioning error was 1.36 m.

The emerging paradigm of “fusion of lifeforms” represents a transformative shift from conventional human–machine interfaces toward deeply integrated symbiotic systems, where biological and artificial components co-adapt structurally, energetically, informationally, and cognitively. This review systematically classifies multi-level perception systems within fusion of lifeforms into four functional categories: sensory and functional restoration, beyond-natural sensing, endogenous state sensing, and cognitive enhancement. We survey recent advances in neuroprosthetics, sensory augmentation, closed-loop physiological monitoring, and brain–computer interfaces, highlighting the transition from substitution to fusion. Despite significant progress, critical challenges remain, including multi-source heterogeneous integration, bandwidth and latency limitations, power and thermal constraints, biocompatibility, and system-level safety. We propose future directions such as layered in-body communication networks, sustainable energy strategies, advanced biointerfaces, and robust safety frameworks. Ethical considerations regarding self-identity, neural privacy, and legal responsibility are also discussed. This work aims to provide a comprehensive reference and roadmap for the development of next-generation fusion of lifeforms, ultimately steering human–machine integration from episodic functional repair toward sustained, multi-level symbiosis between biological and artificial systems.

Heterogeneous unmanned ground vehicle-unmanned aerial vehicle (UGV-UAV) collaborative systems offer clear advantages for field exploration. However, when tethered unmanned aerial vehicles (TUAVs) are introduced to extend mission capability, a major compatibility gap emerges for small and highly maneuverable UGVs: existing industrial tethered ground stations are generally too heavy and bulky to be carried by such platforms. In addition, on unstructured ground, residual station tilt can significantly complicate UAV launch and recovery. To address these issues, this paper develops an ultralight vehicle-mounted tethered ground station for micro unmanned aerial vehicles (micro-UAVs) that can be integrated directly with small UGVs. Through co-design of a 2-degree-of-freedom (2-DOF) self-leveling launch platform and a passive tether-assisted recovery scheme without visual fiducials, in which a customized UAV flight-control loop is coordinated with the state transitions of the ground tether-management system, the proposed system achieves practical tether-assisted recovery. Experiments show that the complete platform weighs only 4.1 kg and that the self-leveling mechanism compensates for ground inclinations over a total range of 24 degrees. Repeated passive-landing tests further demonstrate the feasibility of the proposed recovery scheme and its tolerance to moderate bay tilt and terminal off-axis activation. System-level flight validation confirms practical tether-assisted recovery without visual fiducials. In addition, we conduct a simplified exploratory simulation of tether-based ground-anchor localization under the proposed system architecture. Overall, these results establish a lightweight and low-cost hardware design and a practically viable recovery strategy for multimodal micro air-ground robotic systems.

Visually impaired people face urban mobility hazards such as vehicles, pedestrians, curbs, and steps. Wearable electronic travel aids can support obstacle avoidance only when these hazards fall within sensing coverage. Existing studies have focused mainly on algorithms and human–computer interaction, while the sensing coverage required by real-world hazards remains less examined. We collected 1486 min of street-scene video, built urban mobility hazard samples, and used simulation to compare target pixel counts over time for cameras with different horizontal fields of view. Among 81,353 valid samples, hazards showed concentrated high-frequency categories and a rich long tail, mainly including vehicles, scooters, pedestrians, curbs, bollards, poles, trees, and steps. Simulation showed that a horizontal field of view of approximately $120°$ balanced pixel coverage and sustained observation. We then built a chest-mounted four-camera prototype and conducted a feasibility demonstration at a real intersection. Camera configuration should therefore be guided by real-world hazard visibility, and coordinated multi-camera coverage is a promising design choice for wearable ETAs in urban environments.