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What is the difference between the various R robust regression functions - lmsreg(), ltsreg(), lmrob(), and rlm()? [closed]

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I am rather new to R and am interested in applying a robust regression technique (due to its ability to better handle outliers and influential data points) to a simple dataset to find good linear and exponential trendlines. The R documentation information on some of the applicable functions is rather complex, as were some of the questions/answers out there that I read through concerning these functions, and so I was hoping that someone could explain the high-level differences between the following robust regression functions, including their relative pros and cons:

  • lmsreg()
  • ltsreg()
  • lmrob()
  • rlm()

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