Leader-follower Robot Research Articles

Framework to Estimate Operating Intention for a Leader–Follower Robot

The teleoperation feature of a leader–follower robot is used to operate the robot in a working environment that is dangerous to the operator. This paper proposes a method for estimating the intended operation of the operator of the leader–follower robot and generating behaviors for the follower robot. By generating partially autonomous robot behavior, our proposed method decreases the burden on the operator and realizes a safe controller that is robust against misoperation or disturbances. Owing to the impact of misoperation on estimation and the potential for unintended movement of the follower robot, our proposed estimation method relies on historical values of intended operation. The proposed method was verified through simulation using real operation inputs to the leader system based on practical scenarios, including misoperation.

Grey-box modelling and fuzzy logic control of a Leader–Follower robot manipulator system: A hybrid Grey Wolf–Whale Optimisation approach

This study presents the development of a grey-box modelling approach and fuzzy logic control for real time trajectory control of an experimental four degree-of-freedom Leader–Follower​ Robot (LFR) manipulator system using a hybrid optimisation algorithm, known as Grey Wolf Optimiser (GWO) - Whale Optimisation Algorithm (WOA). The approach has advantages in achieving an accurate model of the LFR manipulator system, and together with a better trajectory tracking performance. In the first instance, the white box model is formed by modelling the dynamics of the follower manipulator using the Euler–Lagrange formulation. This white-box model is then improved upon by re-tuning the model’s parameters using GWO-WOA and experimental data from the real LFR manipulator system, thus forming the grey-box model. A minimum improvement of 73.9% is achieved by the grey-box model in comparison to the white-box model. In the latter part of this investigation, the developed grey-box model is used for the design, tuning and real-time implementation of a fuzzy PD＋I controller on the experimental LFR manipulator system. A 78% improvement in the total mean squared error is realised after tuning the membership functions of the fuzzy logic controller using GWO-WOA. Experimental results show that the approach significantly improves the trajectory tracking performance of the LFR manipulator system in terms of mean squared error, steady state error and time delay.

Experimental Verification of Method to Estimate Operating Intention for Leader-Follower Robot

A leader-follower robot that maintains the safety of operator by remote control is effective for in extreme environments. The follower robot needs to respond to the motion of the operator, but it is also necessary to estimate the operation intention in order to maintain safety. In this research, during operation under several situations, the current operation intention is estimated from sensory input and the history of operation intention. In addition, the operation target value is determined by the operation intention for the controlling of the follower robot’s motion and some sensors’ values. That the operation target values can be calculated is verified by simulated experiments.

Design and Development of Cockpit for Leader-Follower Robot and Application with Method to Estimate Operating Intention

Design and Development of Cockpit for Leader-Follower Robot and Application with Method to Estimate Operating Intention

Haptic Interface with Twin-Driven MR Fluid Actuator for Teleoperation Endoscopic Surgery System

Magnetorheological fluids (MRFs) are composite materials made of ferromagnetic particles, medium oils, and several types of additives. We have developed an actuation system for the fine haptic control of leader-follower robots. In this study, we developed a haptic interface with two link-type twin-driven MR fluid actuators and two MR fluid brakes for a teleoperation endoscopic surgery system and conducted evaluation tests for a remote operational task with a leader-follower robot system. For evaluations, we adopted the NASA-TLX questionnaire as a subjective assessment method. According to the experimental results, the total success rates were 0.462, 0.333, and 0.591, for the first haptic, middle no-haptic, and second haptic phases, respectively. The force information of the haptic forceps helped users to perceive grasping sensation on their fingers. Statistical analyses on the answers to the questionnaire indicate no significant differences. However, a decreasing tendency in the mental stress in the complicated manipulation tasks for fragile objects is observed.

Optimasi Performansi Pengendalian Robot Swarm menggunakan Logika Fuzzy Tipe 2-Particle Swarm Optimazation

Robot control is currently very helpful for human work to be more effective and efficient both in completion time and in mitigating the risk of work accidents that may occur. This study determines the direction of the robot so that it does not collide with each other and reach the target. Controlling the swarm robot with the leader-follower approach uses Fuzzy Logic Type 2-Particle Swarm Optimization (PSO) to optimise the performance of the swarm robot. The Fuzzy Logic Method Type 2 measures the direction decisions of the leader robot and follower robot using a rule base of 8 rules; the leader-follower robot is given a target. Achieving targets using PSO, the PSO process looks for potential solutions with quality references to reach the target as the optimal solution. The leader-follower modelling has been modelled using kinematic equations and controlling the movement of the robot's trajectory in the form of a simulation that has been carried out. The measurement results based on robot data in an open environment are 110 data, and a square environment is 1342. The measurement results based on robot time in a four-obstacle environment have the fastest time of 10.83 seconds and the longest time environment in an oval environment of 134.9 seconds. The measurement results are based on resources in a free environment of 10.6 kb and a square environment of 49.1 kb. Fuzzy Logic Type 2-PSO has a higher time indicating a stable speed result and judging from the trajectory in avoiding obstacles, and the leader-follower robot has a faster response.

Speed Control for Leader-Follower Robot Formation Using Fuzzy System and Supervised Machine Learning.

Mobile robots are endeavoring toward full autonomy. To that end, wheeled mobile robots have to function under non-holonomic constraints and uncertainty derived by feedback sensors and/or internal dynamics. Speed control is one of the main and challenging objectives in the endeavor for efficient autonomous collision-free navigation. This paper proposes an intelligent technique for speed control of a wheeled mobile robot using a combination of fuzzy logic and supervised machine learning (SML). The technique is appropriate for flexible leader-follower formation control on straight paths where a follower robot maintains a safely varying distance from a leader robot. A fuzzy controller specifies the ultimate distance of the follower to the leader using the measurements obtained from two ultrasonic sensors. An SML algorithm estimates a proper speed for the follower based on the ultimate distance. Simulations demonstrated that the proposed technique appropriately adjusts the follower robot’s speed to maintain a flexible formation with the leader robot.

Verification of Acoustic-Wave-Oriented Simple State Estimation and Application to Swarm Navigation

Cooperative swarming behavior of multiple robots is advantageous for various disaster response activities, such as search and rescue. This study proposes an idea of communication of information between swarm robots, especially for estimating the orientation and direction of each robot, to realize decentralized group behavior. Unlike the conventional camera-based systems, we developed robots equipped with a speaker array system and a microphone system to utilize the time difference of arrival (TDoA). Sound waves outputted by each robot was used to estimate the relative direction and orientation. In addition, we attempt to utilize two characteristics of sound waves in our experiments, namely, diffraction and superposition. This paper also investigates the accuracy of state estimation in cases where the robots output sounds simultaneously and are not visible to each other. Finally, we applied our method to achieve behavioral control of a swarm of five robots, and demonstrated that the leader robot and follower robots exhibit good alignment behavior. Our methodology is useful in scenarios where steps or obstacles are present, in which cases camera-based systems are rendered unusable because they require each robot to be visible to each other in order to collect or share information. Furthermore, camera-based systems require expensive devices and necessitate high-speed image processing. Moreover, our method is applicable for behavioral control of swarm robots in water.

Navigation of Three Cooperative Object-Transportation Robots Using a Multistage Evolutionary Fuzzy Control Approach.

This article proposes a new multistage evolutionary fuzzy control configuration and navigation of three-wheeled robots cooperatively carrying an overhead object in unknown environments. Based on the divide-and-conquer technique, this article proposes a stage-by-stage evolutionary obstacle boundary following (OBF) fuzzy control of each of the three robots through multiobjective continuous ant colony optimization. In the first stage, a set of evolutionary nondominated fuzzy controllers (FCs) for a single robot (a leader robot) in the execution of the OBF behavior is learned. In the second stage, a follower robot is controlled by two evolutionary FCs in combination with a switched compensation FC so that the leader and follower robots can cooperatively transport an object while executing the OBF behavior along obstacles containing corners with right angles. In the third stage, the third robot functions as an accompanying robot and is learned to enter into a predicted triangular formation with the leader-follower robots to transport a larger object while executing the OBF behavior. In the navigation of the three object-transportation robots, a new cooperative behavior supervisor is proposed to coordinate the learned OBF behavior and a target seeking behavior. Successful navigations in simulations and experiments verify the effectiveness of the multistage evolutionary fuzzy control approach and navigation scheme.

Performansi Navigasi Robot Leader-Follower menggunakan Algoritma Logika Fuzzy Interval Tipe 2

A leader-follower robot is used to perform different tasks without continuous human assistance. The movement of robot leader-follower to environment who do not structure, avoid persecution and achieving goals is very difficult. Related to the problem, the robot leader-follower requires navigating robots independently using Interval Fuzzy Logic Type-2 (IFLT) 2 Algorithm. The IFLT 2 algorithm performance is successfully applied to this leader-follower robot, with 8 base rules less than the Fuzzy Logic Type 1 Algorithm. This simulation, the robot successfully moves to avoid obstacles and go hand in hand with the position of the follower robot always following the position of the robot leader.

Leader-Follower Mobile Robots Control Based on Light Source Detection

This paper deals with the leader-following control of multiple autonomous mobile robots based on a new sensing method. In this method, we have mounted a light source on the leader robot and installed a photovoltaic sensor at the front end of the follower robot. The photovoltaic sensor consisting of seven micro solar modules acts as a light sensor for the follower robot which helps it to move in accordance with the leader robot by detecting the light source of the leader robot. From the relative angle measurement and ultrasonic measurement of the relative distance, angle offset and distance information between leader robot and follower robot can be estimated. Then, based on an intuitive control method for angle steering proposed in this paper, the follower robot can be controlled smoothly to achieve leader following purpose. The new leader-following control method could overcome the disadvantages of other existing formation control methods. The experimental results show that the leader following based on light source tracking is a comparatively efficient, accurate, and cost-effective method.

Localization of Leader-Follower Robot Using Extended Kalman Filter

Non-holonomic leader-follower robot must be capable to find its own position in order to be able to navigating autonomously in the environment this problem is known as localization. A common way to estimate the robot pose by using odometer. However, odometry measurement may cause inaccurate result due to the wheel slippage or other small noise sources. In this research, the Extended Kalman Filter (EKF) is proposed to minimize the error or the inaccuracy caused by the odometry measurement. The EKF algorithm works by fusing odometry and landmark information to produce a better estimation. A better estimation acknowledged whenever the estimated position lies close to the actual path, which represents a system without noise. Another experiment is conducted to observe the influence of numbers of landmark to the estimated position. The results show that the EKF technique is effective to estimate the leader pose and orientation pose with small error and the follower has the ability traverse close to leader based-on the actual path.

A bio-inspired electrocommunication system for small underwater robots

Weakly electric fishes (Gymnotid and Mormyrid) use an electric field to communicate efficiently (termed electrocommunication) in the turbid waters of confined spaces where other communication modalities fail. Inspired by this biological phenomenon, we design an artificial electrocommunication system for small underwater robots and explore the capabilities of such an underwater robotic communication system. An analytical model for electrocommunication is derived to predict the effect of the key parameters such as electrode distance and emitter current of the system on the communication performance. According to this model, a low-dissipation, and small-sized electrocommunication system is proposed and integrated into a small robotic fish. We characterize the communication performance of the robot in still water, flowing water, water with obstacles and natural water conditions. The results show that underwater robots are able to communicate electrically at a speed of around 1 k baud within about 3 m with a low power consumption (less than 1 W). In addition, we demonstrate that two leader-follower robots successfully achieve motion synchronization through electrocommunication in the three-dimensional underwater space, indicating that this bio-inspired electrocommunication system is a promising setup for the interaction of small underwater robots.

Distributed Embedded Control Architecture of a Leader-Follower Mobile Robot Formation

Mobile robots have been widely used for the good adaptability, payload capability. Robot cooperation brings benefits for the task in a multi-robot team. In this paper, the modular hardware design of a leader-follower mobile robot team is discussed, including the distributed control architecture and the electronic system of each robot of the team. The basic idea behind this paper is to introduce the design of the hardware and distributed control architecture, which mainly manages the distributed control system, consisting of microcontroller modules connected through a data bus. The research has a potential applying prospect in mobile robot tracing and locating in the future.

Dynamic and kinematic observers for output coordination control of Euler-Lagrange systems: A comparison and applications

This paper compares a dynamic and a kinematic observer approach for output coordination control of mechanical systems formulated in the Euler-Lagrange framework. The observers are designed to estimate missing velocity and acceleration information based on position/attitude measurements to provide a full state vector to the coordination control algorithm. The kinematic observer approach utilizes a virtual system designed to mimic the kinematic behaviour of the leader in order to estimate unknown states of the state vector with a minimum of information available. The dynamic observer approach is based on utilizing the full dynamic model of the follower system when estimating the missing states. The two observers are compared in terms of estimation principles and practical performance, and applied to two practical examples; leader-follower robot manipulator synchronization control, and underway replenishment operations for surface ships.

Human-robot formation control via visual and vibrotactile haptic feedback.

In this paper we present a new visuo-haptic interaction mechanism for human-robot formation control. The formation setup consists of a human leader and multiple follower robots. The mobile robots are equipped only with RGB-D cameras, and they should maintain a desired distance and orientation to the leader at all times. Mechanical limitations common to all the robots limit the possible trajectories that the human can take. In this regard, vibrotactile feedback provided by a haptic bracelet guides the human along trajectories that are feasible for the team by warning her/him when the formation constraints are being violated. Psychophysical tests on the bracelet together with real-world experiments conducted with a team of Pioneer robots show the effectiveness of the proposed visuo-haptic paradigm for the coordination of mixed human-robot teams.

Multi-Robot Formation Control Based on the Artificial Potential Field Method

The artificial potential field method is one of multi-robot formation control methods. In this paper we make a study on multi-robot formation control based on the artificial potential field method and the leader-follower method. The robots are set leader robot and follower robots respectively. According to the known ideal distance between the leader and follower, we adjust the repulsiveness or attractiveness to maintain multi-robot formation. Multi-robots obstacle avoidance is adopted the artificial potential field method. In this paper the triangle formation is taken as an example. At last the simulation result proves the validity of this algorithm.

Multi-Robot Formation Control Based on the Artificial Potential Field Method

The artificial potential field method is one of multi-robot formation control methods. In this paper we make a study on multi-robot formation control based on the artificial potential field method and the leader-follower method. The robots are set leader robot and follower robots respectively. According to the known ideal distance between the leader and follower, we adjust the repulsiveness or attractiveness to maintain multi-robot formation. Multi-robots obstacle avoidance is adopted the artificial potential field method. In this paper the triangle formation is taken as an example. At last the simulation result proves the validity of this algorithm.

리더-추종자 대형제어의 장애물 회피

This paper presents obstacle avoidance of Leader-Follower formation. The follower robot maintain the formation with leader robot and avoid the detected obstacle. When obstacle is detected, follower robot avoid it considering leader robot and follower robot position and follower robot and obstacle position. In addition, follower robot avoid obstacle irrespective of obstacle size. Controller of follower robot is designed to satisfy Lyapunov stability by backstepping method. Simulation results shows that the designed controller has a stable performance.

A model-based fault tolerant control design for nonholonomic mobile robots in formation

In this paper, a new model-based fault tolerant kinematic/torque control law is developed by using backstepping for leader-follower robots in formation. In comparison to the kinematic-based formation controllers, the proposed control law design considers the dynamics of the robots and the formation. Initially, the control law is developed for leader and follower mobile robots under normal operation (i.e., no faults); the stability of the formation is verified using Lyapunov theory. Later, an online model-based fault tolerant design is introduced in the presence of a fault, where the fault could be incipient or abrupt in nature. In other words, the fault is mitigated by adding an extra term into the existing control law, which is a function of the unknown fault dynamics, recovered using a neural network. Using Lyapunov theory, the stability of the fault tolerant control law and the formation errors are guaranteed to converge asymptotically in the presence of faults and system uncertainties. Finally, numerical results are used to verify the theoretical results presented in the paper.