Algorithm
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An algorithm is a precise, step-by-step computational procedure that takes defined inputs and produces desired outputs through a finite sequence of well-specified operations. In robotics and AI, algorithms form the foundational building blocks for virtually every capability a system exhibits — from path planning and motion control to perception, localization, and learning. Robots rely on algorithms to navigate environments (probabilistic roadmaps, SLAM), estimate their state (particle filters, Kalman filters), recognize objects (computer vision pipelines), and make decisions (reinforcement learning, planning frameworks). The efficiency, correctness, and robustness of an algorithm directly determine whether a robotic system can operate reliably in real-world conditions under time and resource constraints. Algorithms matter because they translate mathematical theory into practical, executable behavior: a well-designed algorithm can make an otherwise intractable problem — such as motion planning in high-dimensional spaces or real-time sensor fusion — computationally feasible. Understanding algorithmic principles allows engineers and researchers to analyze performance guarantees, identify bottlenecks, and adapt existing methods to new problems across the full spectrum of robotics and AI applications.
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Probabilistic roadmaps for path planning in high-dimensional configuration spaces
Lydia E. Kavraki, P. Švestka, J.-C. Latombe, M.H. Overmars
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A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses
R. Tsai
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Jean‐Claude Latombe
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Steven M. LaValle
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Closed-form solution of absolute orientation using unit quaternions
Berthold K. P. Horn
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Simultaneous localization and mapping: part I
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Real-Time Computing Without Stable States: A New Framework for Neural Computation Based on Perturbations
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Robert M. Haralock, Linda G. Shapiro
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The university of Florida sparse matrix collection
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Hierarchical Mixtures of Experts and the EM Algorithm
Michael I. Jordan, Robert A. Jacobs
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Robust Adaptive Control of Feedback Linearizable MIMO Nonlinear Systems With Prescribed Performance
Charalampos P. Bechlioulis, George A. Rovithakis
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Principles of Robot Motion: Theory, Algorithms, and Implementations
Howie Choset, Jean‐Claude Latombe
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FastSLAM: a factored solution to the simultaneous localization and mapping problem
Michael Montemerlo, Sebastian Thrun, Daphne Koller, Ben Wegbreit
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G<sup>2</sup>o: A general framework for graph optimization
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Soft Actor-Critic Algorithms and Applications
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Robust Monte Carlo localization for mobile robots
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Tracking control of non-linear systems using sliding surfaces, with application to robot manipulators†
J.-J.E. Slotine, Shankar Sastry
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