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  2. Motion planning - Wikipedia

    en.wikipedia.org/wiki/Motion_planning

    A basic motion planning problem is to compute a continuous path that connects a start configuration S and a goal configuration G, while avoiding collision with known obstacles. The robot and obstacle geometry is described in a 2D or 3D workspace , while the motion is represented as a path in (possibly higher-dimensional) configuration space .

  3. Code motion - Wikipedia

    en.wikipedia.org/wiki/Code_motion

    A diagram depicting an optimizing compiler removing a potentially useless call to assembly instruction "b" by sinking it to its point of use. Code Sinking, also known as lazy code motion, is a term for a technique that reduces wasted instructions by moving instructions to branches in which they are used: [1] If an operation is executed before a branch, and only one of the branch paths use the ...

  4. Loop-invariant code motion - Wikipedia

    en.wikipedia.org/wiki/Loop-invariant_code_motion

    In computer programming, loop-invariant code consists of statements or expressions (in an imperative programming language) that can be moved outside the body of a loop without affecting the semantics of the program. Loop-invariant code motion (also called hoisting or scalar promotion) is a compiler optimization that performs this movement ...

  5. Python (programming language) - Wikipedia

    en.wikipedia.org/wiki/Python_(programming_language)

    Guido van Rossum began working on Python in the late 1980s as a successor to the ABC programming language and first released it in 1991 as Python 0.9.0. [36] Python 2.0 was released in 2000. Python 3.0, released in 2008, was a major revision not completely backward-compatible with earlier versions.

  6. Nuitka - Wikipedia

    en.wikipedia.org/wiki/Nuitka

    Nuitka (pronounced as / n juː t k ʌ / [2]) is a source-to-source compiler which compiles Python code to C source code, applying some compile-time optimizations in the process such as constant folding and propagation, built-in call prediction, type inference, and conditional statement execution.

  7. Falling cat problem - Wikipedia

    en.wikipedia.org/wiki/Falling_cat_problem

    A solution of the falling cat problem is a curve in the configuration space that is horizontal with respect to the connection (that is, it is admissible by the physics) with prescribed initial and final configurations. Finding an optimal solution is an example of optimal motion planning. [11] [12]

  8. Constraint programming - Wikipedia

    en.wikipedia.org/wiki/Constraint_programming

    Constraint propagation in constraint satisfaction problems is a typical example of a refinement model, and formula evaluation in spreadsheets are a typical example of a perturbation model. The refinement model is more general, as it does not restrict variables to have a single value, it can lead to several solutions to the same problem.

  9. Range of a projectile - Wikipedia

    en.wikipedia.org/wiki/Range_of_a_projectile

    The first solution corresponds to when the projectile is first launched. The second solution is the useful one for determining the range of the projectile. Plugging this value for (t) into the horizontal equation yields = ⁡ ⁡ Applying the trigonometric identity