Goal-Oriented Vision-and-Language Navigation (VLN) aims to enable agents to navigate to specified locations and identify designated target objects following natural language instruction. This approach has gained popularity due to its close alignment with real-world scenarios. However, existing studies have predominantly focused on enhancing navigation performance, neglecting the ability to locate objects at the navigation endpoint. This oversight has resulted in a significant discrepancy between the success rates of navigation and object grounding. The challenge is compounded by the complex reasoning required by the instructions and the necessity to synthesize multiperspective images of objects, which overwhelms traditional object grounding methods. We leverage the Multi-Modal Large Language Model (MLLM) to bridge this gap, allowing agents to seek assistance from these models when struggling to locate the target object. The agent conducts a multi-stage evaluation to discern the cause of its confusion and promptly extracts and updates the most relevant information for MLLM to assess. Our method is plug-and-play and model-agnostic, facilitating integration with numerous existing VLN strategies without the need for retraining. Implementing our approach across four distinct methods has improved performance on the REVERIE and SOON datasets, demonstrating the effectiveness and generalizability of our technique.

In this paper, a power quality (PQ) survey of the large-power electrolytic manganese factory is presented to provide the background introduction of PQ issues. The electrolytic manganese factory consists of 10 rectifier units, which has the electric environment of large current/low voltage. The monitoring object is a 15 MVA rectifier unit. The power quality monitoring lasted 16.5 hours. First, the topology of the large-power supply system is introduced. Then, the measuring results are analyzed in detail, which include the power factor and harmonic. At last, a case study of power quality issue is illustrated, and the recommended solution is given out. The test results indicate that the power quality can meet the relevant requirements with the help of harmonic filter.