Non-rigid formations of nonholonomic robots

In this paper, we propose a control strategy for a nonholonomic robot which is based on an Adaptive Neural Fuzzy Inference System. The neuro-controller makes it possible the robot track a desired reference trajectory. After a short reminder about Adaptive Neural Fuzzy Inference System, we describe the control strategy which is used on our virtual nonholonomic robot. And finally, we give the simulations’ results where the robot have to pass into a narrow path as well as the first validation results concerning the implementation of the proposed concepts on real robot.

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Stabilizing Angle Rigid Formations with Prescribed Orientation and Scale

IEEE Transactions on Industrial Electronics ◽

10.1109/tie.2021.3120476 ◽

2021 ◽

pp. 1-1

Author(s):

Liangming Chen ◽

Qingkai Yang ◽

Mingming Shi ◽

Yanan Li ◽

Mir Feroskhan

Keyword(s):

Rigid Formations

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Local Path-Tracking Strategies for Mobile Robots Using PID Controllers

Mobile Ad Hoc Robots and Wireless Robotic Systems - Advances in Computational Intelligence and Robotics ◽

10.4018/978-1-4666-2658-4.ch003 ◽

2013 ◽

pp. 58-79

Author(s):

Lluis Pacheco ◽

Ningsu Luo

Keyword(s):

Mobile Robot ◽

Mobile Robots ◽

Path Following ◽

Research Topic ◽

Pid Controllers ◽

Good Communication ◽

Nonholonomic Robots ◽

Robot Positioning ◽

Local Path ◽

Control Methodology

Accurate path following is an important mobile robot research topic. In many cases, radio controlled robots are not able to work properly due to the lack of a good communication system. This problem can cause many difficulties when robot positioning is regarded. In this context, gaining automatic abilities becomes essential to achieving a major number of mission successes. This chapter presents a suitable control methodology used to achieve accurate path following and positioning of nonholonomic robots by using PID controllers. An important goal is to present the obtained experimental results by using the available mobile robot platform that consists of a differential driven one.

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EXTENDING TEACH–REPEAT TO NONHOLONOMIC ROBOTS

Structronic Systems: Smart Structures, Devices and Systems - Series on Stability, Vibration and Control of Systems, Series B ◽

10.1142/9789812817358_0018 ◽

1998 ◽

pp. 316-342 ◽

Cited By ~ 2

Author(s):

Steven B. Skaar ◽

John–David Yoder

Keyword(s):

Nonholonomic Robots

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Modified Newton's method applied to potential field based navigation for nonholonomic robots in dynamic environments

Robotica ◽

10.1017/s026357470700389x ◽

2008 ◽

Vol 26 (3) ◽

pp. 285-294 ◽

Cited By ~ 6

Author(s):

Jing Ren ◽

Kenneth A. McIsaac ◽

Rajni V. Patel

Keyword(s):

Newton’S Method ◽

Potential Field ◽

Newton's Method ◽

Dynamic Environment ◽

Dynamic Environments ◽

Field Methods ◽

Control Laws ◽

Nonholonomic Robots ◽

Modified Newton’S Method ◽

Speed Up

SUMMARYThis paper is to investigate inherent oscillations problems of Potential Field Methods (PFMs) for nonholonomic robots in dynamic environments. In prior work, we proposed a modification of Newton's method to eliminate oscillations for omnidirectional robots in static environment. In this paper, we develop control laws for nonholonomic robots in dynamic environment using modifications of Newton's method. We have validated this technique in a multirobot search-and-forage task. We found that the use of the modifications of Newton's method, which applies anywhere C2 continuous navigation functions are defined, can greatly reduce oscillations and speed up robot's movement, when compared to the standard gradient approaches.

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A Geometric Path Planner for Car-like Robots

Journal of Mechanical Design ◽

10.1115/1.1288403 ◽

1999 ◽

Vol 122 (3) ◽

pp. 343-346 ◽

Cited By ~ 1

Author(s):

Shiang-Fong Chen ◽

Jiansong Deng

Keyword(s):

Kinematic Constraints ◽

Nonholonomic Robots ◽

Path Planner ◽

Flying Robots

This technical brief presents a refined slabbing method, originally used for free-flying robots, for finding efficient paths for nonholonomic robots. Our method takes kinematic constraints and reversal maneuvers into account. We create orientation levels for each orientation configuration of the robot. The slopes of slabbing lines in each orientation level match the orientation of a robot in that level. The resulting slabbing lines act as “rails” to guide the robot. Thus, a robot, if it keeps moving in a given orientation level, can only translate straight forward or straight backward along a given slabbing line. Limiting robot movement to straight forward or straight backward along a slabbing line prevents the robot from violating kinematic constraints, by moving sideways to another slabbing line. [S1050-0472(00)01403-3]

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