Control (management)
Related papers: 20
About
Control, in the context of robotics and AI, refers to the mathematical methods and engineering techniques used to command, regulate, and stabilize the behavior of robotic systems so they achieve desired outcomes reliably and accurately. It encompasses a broad range of approaches—from classical feedback loops and PID controllers to advanced nonlinear, adaptive, and sliding mode methods—that translate high-level task goals into precise actuator commands governing a robot's motion, force, and interaction with its environment. In robotics, control is applied across manipulator arms, mobile platforms, legged robots, and multi-agent systems, addressing challenges such as trajectory tracking, obstacle avoidance, compliant force regulation, and balance during locomotion. Techniques like operational space formulation, visual servoing, and iterative learning control allow robots to handle complex, real-world dynamics. Multi-agent coordination extends these principles to teams of robots acting collectively. Control matters because even a mechanically perfect robot is useless without the algorithms that make it move safely, accurately, and adaptively. As robots operate in increasingly unstructured and dynamic environments, robust and intelligent control strategies are the critical bridge between physical hardware and intelligent, purposeful behavior.
Top Researchers
Top Cited Papers
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
Citations: 18993 • 1991
Real-Time Obstacle Avoidance for Manipulators and Mobile Robots
Oussama Khatib
Citations: 7533 • 1986
Introduction to Robotics mechanics and Control
John Craig
Citations: 5039 • 1986
Robot dynamics and control
Mark W. Spong
Citations: 3821 • 1989
Bettering operation of Robots by learning
Suguru Arimoto, Sadao Kawamura, Fumio Miyazaki
Citations: 3445 • 1984
Robot Modeling and Control
Mark W. Spong, Seth Hutchinson, M. Vidyasagar
Citations: 3281 • 2006
Randomized Kinodynamic Planning
Steven M. LaValle, James Kuffner
Citations: 3241 • 2001
Sliding Mode Control in Electro-Mechanical Systems
Vadim Utkin, Jürgen Guldner, Jingxin Shi
Citations: 3211 • 2010
Hybrid Position/Force Control of Manipulators
Marc H. Raibert, John Craig
Citations: 2978 • 1981
A unified approach for motion and force control of robot manipulators: The operational space formulation
Oussama Khatib
Citations: 2917 • 1987
Robot Manipulators: Mathematics, Programming, and Control
Richard P. Paul
Citations: 2813 • 1981
Distributed Consensus in Multi-vehicle Cooperative Control
Wei Ren, Randal W. Beard
Citations: 2761 • 2007
Legged Robots That Balance
Marc H. Raibert, Ernest R. Tello
Citations: 2724 • 1986
Adaptive representation of dynamics during learning of a motor task
Reza Shadmehr, FA Mussa-Ivaldi
Citations: 2666 • 1994
Proceedings of the 2004 American Control Conference
Citations: 2614 • 2004
Continuous finite-time control for robotic manipulators with terminal sliding mode
Shuanghe Yu, Xinghuo Yu, Bijan Shirinzadeh, Zhihong Man
Citations: 2605 • 2005
Robust Adaptive Control of Feedback Linearizable MIMO Nonlinear Systems With Prescribed Performance
Charalampos P. Bechlioulis, George A. Rovithakis
Citations: 2576 • 2008
Manipulability of Robotic Mechanisms
Tsuneo Yoshikawa
Citations: 2516 • 1985
Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach
Kazuo Tanaka, Hua O. Wang
Citations: 2454 • 2008
Visual servo control. I. Basic approaches
François Chaumette, Seth Hutchinson
Citations: 2431 • 2006