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Soft rod-climbing robots have been known to have great potential in a wide variety of working conditions, including cable inspection and pipeline maintenance. However, one of the most notable issues preventing their popular adoption is their inability to effectively cross obstacles or transfer between rods. To overcome these difficulties, this paper aims to propose an inchworm-inspired soft robot with omni-directional steering.

Theoretical models are first established to analyze the telescopic deformation, bending, steering and climbing ability of the soft robot. The main modes of movement the soft robot is expected to encounter is then determined through controlled testing so to verify their effectiveness (those being rod climbing, steering and obstacle surmounting).

The soft robot demonstrated a capability to cross obstacles 1.3 times its own width and bend 120° omni-directionally, evidencing outstanding abilities in both omni-directional steering and obstacle surmounting. In addition, the soft robot also exhibited acceptable climbing performance in a variety of working conditions such as climbing along vertical rods, transferring between rods with differing diameters or friction surfaces and bearing a payload.

The soft robot proposed in this paper possesses abilities that are both exceptional and crucial for practical use, specifically with regard to its omni-directional steering and obstacle surmounting.

This study aims to adopt a systematic review approach to examine the existing literature on law and LLMs.It involves analyzing and synthesizing relevant research papers, reports and scholarly articles that discuss the use of LLMs in the legal domain. The review encompasses various aspects, including an analysis of LLMs, legal natural language processing (NLP), model tuning techniques, data processing strategies and frameworks for addressing the challenges associated with legal question-and-answer (Q&A) systems. Additionally, the study explores potential applications and services that can benefit from the integration of LLMs in the field of intelligent justice.

This paper surveys the state-of-the-art research on law LLMs and their application in the field of intelligent justice. The study aims to identify the challenges associated with developing Q&A systems based on LLMs and explores potential directions for future research and development. The ultimate goal is to contribute to the advancement of intelligent justice by effectively leveraging LLMs.

To effectively apply a law LLM, systematic research on LLM, legal NLP and model adjustment technology is required.

This study contributes to the field of intelligent justice by providing a comprehensive review of the current state of research on law LLMs.