Collision
Related papers: 20
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Collision, in the context of robotics and AI, refers to the undesired physical contact between a robot and obstacles, other robots, humans, or environmental structures. Understanding and managing collisions encompasses detection, avoidance, and reaction — forming a foundational challenge across nearly all robotic systems. Collision avoidance techniques, such as artificial potential fields, dynamic window approaches, velocity obstacles, and reciprocal velocity methods, enable robots to plan and execute paths that sidestep obstacles in real time, even in dynamic or crowded environments. Collision detection methods allow robots to sense unexpected contact through force/torque signals or model-based estimation, triggering safe reactive behaviors. In multi-robot systems, decentralized and learning-based approaches extend these capabilities to coordinated, collision-free navigation among many agents. Collision matters profoundly in robotics because it directly governs safety — particularly in human-robot interaction — as well as operational efficiency and system reliability. Whether guiding a manipulator arm, navigating an autonomous vehicle, or coordinating drone swarms, robust collision management is essential for deploying robots in real-world, unstructured environments alongside people.
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Top Cited Papers
Real-Time Obstacle Avoidance for Manipulators and Mobile Robots
Oussama Khatib
Citations: 7533 • 1986
The dynamic window approach to collision avoidance
D. Fox, Wolfram Burgard, Sebastian Thrun
Citations: 3622 • 1997
The vector field histogram-fast obstacle avoidance for mobile robots
J. Borenstein, Yoram Koren
Citations: 2278 • 1991
Motion Planning in Dynamic Environments Using Velocity Obstacles
Paolo Fiorini, Zvi Shiller
Citations: 1930 • 1998
Reciprocal n-Body Collision Avoidance
Jur van den Berg, Stephen J. Guy, Ming–Chieh Lin, Dinesh Manocha
Citations: 1811 • 2011
Real-time obstacle avoidance for manipulators and mobile robots
Oussama Khatib
Citations: 1684 • 2005
Real-Time Obstacle Avoidance for Manipulators and Mobile Robots
Oussama Khatib
Citations: 1557 • 1986
Motion planning with sequential convex optimization and convex collision checking
John Schulman, Yan Duan, Jonathan Ho, Alex Pui‐Wai Lee, Ibrahim Awwal, Henry Bradlow, Jia Pan, Sachin Patil, Ken Goldberg, Pieter Abbeel
Citations: 840 • 2014
Full control of a quadrotor
Samir Bouabdallah, Roland Siegwart
Citations: 796 • 2007
Collision Detection and Safe Reaction with the DLR-III Lightweight Manipulator Arm
Alessandro De Luca, Alin Albu‐Schäffer, Sami Haddadin, Gerd Hirzinger
Citations: 763 • 2006
Robot Collisions: A Survey on Detection, Isolation, and Identification
Sami Haddadin, Alessandro De Luca, Alin Albu‐Schäffer
Citations: 754 • 2017
Safety Barrier Certificates for Collisions-Free Multirobot Systems
Li Wang, Aaron D. Ames, Magnus Egerstedt
Citations: 747 • 2017
Literature survey of contact dynamics modelling
Gabriele Gilardi, Inna Sharf
Citations: 719 • 2002
Socially aware motion planning with deep reinforcement learning
Yu Fan Chen, Michael Everett, Miao Liu, Jonathan P. How
Citations: 715 • 2017
Rigid-Body Dynamics with Friction and Impact
David E. Stewart
Citations: 622 • 2000
Collision Detection and Reaction: A Contribution to Safe Physical Human-Robot Interaction
Sami Haddadin, Alin Albu‐Schäffer, Alessandro De Luca, Gerd Hirzinger
Citations: 560 • 2008
Obstacle avoidance in a dynamic environment: a collision cone approach
Animesh Chakravarthy, Debasish Ghose
Citations: 545 • 1998
Swarm of micro flying robots in the wild
Xin Zhou, Xiangyong Wen, Zhepei Wang, Yuman Gao, Haojia Li, Qianhao Wang, Tiankai Yang, Haojian Lu, Yanjun Cao, Chao Xu, Fei Gao
Citations: 539 • 2022
FCL: A general purpose library for collision and proximity queries
Jia Pan, Sachin Chitta, Dinesh Manocha
Citations: 537 • 2012
High-speed navigation using the global dynamic window approach
Oliver Brock, Oussama Khatib
Citations: 536 • 2003