IEEE

A General, Fast, and Robust Implementation of the Time-Optimal Path Parameterization Algorithm

Abstract: Finding the time-optimal parameterization of a given path subject to kinodynamic constraints is an essential component in many robotic theories and applications. The objective of this paper ...
GitHub

Python implementation of the TurboQuant and QJL vector quantization algorithms.

turboquant-py implements the TurboQuant and QJL vector quantization algorithms from Google Research (ICLR 2026 / AISTATS 2026). It compresses high-dimensional floating-point vectors to 1-4 bits per ...
GitHub

Making a Class Schedule Using a Genetic Algorithm with Python

Making a class schedule is one of those NP hard problems. The problem can be solved using a heuristic search algorithm to find the optimal solution, but it only works for simple cases. For more ...
Scientific Research Publishing

Complete Coverage Path Planning Based on Improved Area Division ()

1 Transportation Engineering College, Dalian Maritime University, Dalian, China. 2 School of Maritime Economics and Management, Dalian Maritime University, Dalian, China. With the development of the ...
Scientific Research Publishing

Multi-Strategy-Driven Salp Swarm Algorithm for Global Optimization ()

In response to the shortcomings of the Salp Swarm Algorithm (SSA) such as low convergence accuracy and slow convergence speed, a Multi-Strategy-Driven Salp Swarm Algorithm (MSD-SSA) was proposed.
Frontiers

Comparing Deep Reinforcement Learning Algorithms’ Ability to Safely Navigate Challenging Waters

Reinforcement Learning (RL) controllers have proved to effectively tackle the dual objectives of path following and collision avoidance. However, finding which RL algorithm setup optimally trades off ...