Heuristic
Related papers: 20
About
A heuristic is a problem-solving strategy or rule of thumb that guides search and decision-making processes toward good solutions efficiently, without guaranteeing mathematical optimality. In robotics and AI, heuristics are used extensively in path planning, motion planning, and navigation—for example, A* and D* Lite use heuristic cost estimates to prioritize which states to explore, dramatically reducing computation time compared to exhaustive search. Heuristics also appear in bio-inspired algorithms such as ant colony optimization and harmony search, where problem-solving rules mimic natural behaviors to find near-optimal solutions for complex planning tasks. In coverage path planning, obstacle avoidance, and multi-robot coordination, heuristics enable robots to operate effectively under real-time constraints and incomplete environmental knowledge. Their importance lies in making otherwise intractable problems computationally feasible: robots must make rapid decisions in dynamic, uncertain environments where exact solutions would be too slow or resource-intensive. While heuristic solutions may sacrifice guaranteed optimality, they provide practical, scalable approaches that are central to modern autonomous robotics systems.
Top Researchers
Top Institutes
Top Cited Papers
Machine learning a probabilistic perspective
Kevin P. Murphy
Citations: 9328 • 2012
Motion Planning in Dynamic Environments Using Velocity Obstacles
Paolo Fiorini, Zvi Shiller
Citations: 1930 • 1998
Coverage for robotics – A survey of recent results
Howie Choset
Citations: 1189 • 2001
Toward Efficient Trajectory Planning: The Path-Velocity Decomposition
Kamal Kant, Steven W. Zucker
Citations: 753 • 1986
Fast replanning for navigation in unknown terrain
Sven Koenig, Maxim Likhachev
Citations: 679 • 2005
Heuristic approaches in robot path planning: A survey
Cosmin Copot, Duc Trung Tran, Robin De Keyser
Citations: 631 • 2016
Dynamic Movement Primitives -A Framework for Motor Control in Humans and Humanoid Robotics
Stefan Schaal
Citations: 602 • 2006
ARA*: Anytime A* with Provable Bounds on Sub-Optimality
Maxim Likhachev, Geoffrey J. Gordon, Sebastian Thrun
Citations: 595 • 2003
Path planning optimization of indoor mobile robot based on adaptive ant colony algorithm
Changwei Miao, Guangzhu Chen, Chengliang Yan, Yuanyuan Wu
Citations: 469 • 2021
Acting under uncertainty: discrete Bayesian models for mobile-robot navigation
Anthony R. Cassandra, Leslie Pack Kaelbling, James Kurien
Citations: 468 • 2002
6D SLAM—3D mapping outdoor environments
Andreas Nüchter, Kai Lingemann, Joachim Hertzberg, Hartmut Surmann
Citations: 446 • 2007
Adaptive Locomotion of a Multilegged Robot over Rough Terrain
Robert B. McGhee, Geoffrey I. Iswandhi
Citations: 406 • 1979
D*lite
Sven Koenig, Maxim Likhachev
Citations: 394 • 2002
Path planning for autonomous mobile robot navigation with ant colony optimization and fuzzy cost function evaluation
Mário Garcia, Oscar Montiel, Oscar Castillo, Roberto Sepúlveda, Patricia Melín
Citations: 392 • 2009
VFH/sup */: local obstacle avoidance with look-ahead verification
Iwan Ulrich, J. Borenstein
Citations: 384 • 2002
SAPIEN: A SimulAted Part-Based Interactive ENvironment
Fanbo Xiang, Yuzhe Qin, Kaichun Mo, Yikuan Xia, Hao Zhu, Fangchen Liu, Minghua Liu, Hanxiao Jiang, Yifu Yuan, He Wang, Yi Li, Anne Lynn S. Chang, Leonidas Guibas, Hao Su
Citations: 373 • 2020
A survey on applications of the harmony search algorithm
Diana Manjarrés, Itziar Landa-Torres, Sergio Gil-López, Javier Del Ser, Miren Nekane Bilbao, Sancho Salcedo‐Sanz, Zong Woo Geem
Citations: 364 • 2013
Control of robotic mobility-on-demand systems: A queueing-theoretical perspective
Rick Zhang, Marco Pavone
Citations: 364 • 2015
Real-time randomized path planning for robot navigation
James Bruce, Manuela Veloso
Citations: 318 • 2003
A Comprehensive Review of Coverage Path Planning in Robotics Using Classical and Heuristic Algorithms
Chee Sheng Tan, Rosmiwati Mohd‐Mokhtar, Mohd Rizal Arshad
Citations: 313 • 2021