Visual-Servoing Based Global Path Planning Using Interval Type-2 Fuzzy Logic Control

Mobile Robot Control Based on 3D Visual Servoing: A New Approach Combining Pose Estimation by Neural Network and Differential Flatness

This paper deals with 3D visual servoing applied to mobile robots in the presence of measurement disturbances, caused in particular by target occlusion. We propose a new approach based on the flatness concept. In 3D visual servoing, the task is performed out of image coordinate space and targets may leave the camera field of view during navigation (servoing). Forced to navigate blindly during one or more periods of time, the robot will use our new open-loop control algorithm inspired by the flatness concept. The 3D visual servoing method is performed using robot pose estimation. This estimation generally contains some errors. The exact position of the robot is therefore not guaranteed, and robust feedback control is necessary to reject these errors in the input. To solve this problem, we propose a new pose estimation method that uses neural networks. We reduce the complexity of the architecture of the neural networks used (the number of variables to estimate) by proving that the location and the orientation of the robot can be ensured by using a single point in the image coordinate space for mobile robots with two degrees of freedom. To show the efficiency of the proposed algorithm, we use the RVCTOOLS MATLAB toolbox.

A Consolidated Review of Path Planning and Optimization Techniques: Technical Perspectives and Future Directions

In this paper, a review on the three most important communication techniques (ground, aerial, and underwater vehicles) has been presented that throws light on trajectory planning, its optimization, and various issues in a summarized way. This kind of extensive research is not often seen in the literature, so an effort has been made for readers interested in path planning to fill the gap. Moreover, optimization techniques suitable for implementing ground, aerial, and underwater vehicles are also a part of this review. This paper covers the numerical, bio-inspired techniques and their hybridization with each other for each of the dimensions mentioned. The paper provides a consolidated platform, where plenty of available research on-ground autonomous vehicle and their trajectory optimization with the extension for aerial and underwater vehicles are documented.

Samarakoon SMB, Muthugala MAVJ, Elara MR. Design of a Reconfigurable Wall Disinfection Robot

During a viral outbreak, such as COVID-19, autonomously operated robots are in high demand. Robots effectively improve the environmental concerns of contaminated surfaces in public spaces, such as airports, public transport areas and hospitals, that are considered high-risk areas. Indoor spaces walls made up most of the indoor areas in these public spaces and can be easily contaminated. Wall cleaning and disinfection processes are therefore critical for managing and mitigating the spread of viruses. Consequently, wall cleaning robots are preferred to address the demands. A wall cleaning robot needs to maintain a close and consistent distance away from a given wall during cleaning and disinfection processes. In this paper, a reconfigurable wall cleaning robot with autonomous wall following ability is proposed. The robot platform, Wasp, possess inter-reconfigurability, which enables it to be physically reconfigured into a wall-cleaning robot. The wall following ability has been implemented using a Fuzzy Logic System (FLS). The design of the robot and the FLS are presented in the paper. The platform and the FLS are tested and validated in several test cases. The experimental outcomes validate the real-world applicability of the proposed wall following method for a wall cleaning robot.

A novel navigation system for an autonomous mobile robot in an uncertain environment

In this paper, we developed a new navigation system, called ATCM, which detects obstacles in a sliding window with an adaptive threshold clustering algorithm, classifies the detected obstacles with a decision tree, heuristically predicts potential collision and finds optimal path with a simplified Morphin algorithm. This system has the merits of optimal free-collision path, small memory size and less computing complexity, compared with the state of the arts in robot navigation. The modular design of 6-steps navigation provides a holistic methodology to implement and verify the performance of a robot’s navigation system. The experiments on simulation and a physical robot for the eight scenarios demonstrate that the robot can effectively and efficiently avoid potential collisions with any static or dynamic obstacles in its surrounding environment. Compared with the particle swarm optimisation, the dynamic window approach and the traditional Morphin algorithm for the autonomous navigation of a mobile robot in a static environment, ATCM achieved the shortest path with higher efficiency.

Collision Avoidance and Stability Study of a Self-Reconfigurable Drainage Robot

The inspection and maintenance of drains with varying heights necessitates a drain mapping robot with trained labour to maintain community hygiene and prevent the spread of diseases. For adapting to level changes and navigating in the narrow confined environments of drains, we developed a self-configurable hybrid robot, named Tarantula-II. The platform is a quadruped robot with hybrid locomotion and the ability to reconfigure to achieve variable height and width. It has four legs, and each leg is made of linear actuators and modular rolling wheel mechanisms with bi-directional movement. The platform has a fuzzy logic system for collision avoidance of the side wall in the drain environment. During level shifting, the platform achieves stability by using the pitch angle as the feedback from the inertial measuring unit (IMU) mounted on the platform. This feedback helps to adjust the accurate height of the platform. In this paper, we describe the detailed mechanical design and system architecture, kinematic models, control architecture, and stability of the platform. We deployed the platform both in a lab setting and in a real-time drain environment to demonstrate the wall collision avoidance, stability, and level shifting capabilities of the platform.

Motion and trajectory planning modeling for mobile landing mechanism systems based on improved genetic algorithm

In many traditional soft-landing missions, researchers design the lander and the rover as two separate individuals, which has its limitations. At present, research on landers mainly focuses on the performance analysis of those who cannot move, and the motion of legged mobile lander has not yet been studied. In this paper, a novel Mobile Landing Mechanism (MLM) is proposed. Firstly, the monte-Carlo method is used to solve the workspace, and the motion feasibility of the mechanism is verified. Secondly, combining with the constraints of velocity, acceleration and secondary acceleration of each driving joint of the MLM, the trajectory of its joint space is planned by using cubic spline curve. And based on the weighted coefficient method, an optimal time-jerk pedestal trajectory planning model is established. Finally, by comparing the genetic algorithm (GA) with the adaptive genetic algorithm (AGA), an optimization algorithm is proposed to solve the joint trajectory optimization problem of the MLM, which can obtain better trajectory under constraints. Simulation shows that the motion performance of the mechanism is continuous and stable, which proves the rationality and effectiveness of the foot trajectory planning method.

Wall-Following Behavior for a Disinfection Robot Using Type 1 and Type 2 Fuzzy Logic Systems

Infectious diseases are caused by pathogenic microorganisms, whose transmission can lead to global pandemics like COVID-19. Contact with contaminated surfaces or objects is one of the major channels of spreading infectious diseases among the community. Therefore, the typical contaminable surfaces, such as walls and handrails, should often be cleaned using disinfectants. Nevertheless, safety and efficiency are the major concerns of the utilization of human labor in this process. Thereby, attention has drifted toward developing robotic solutions for the disinfection of contaminable surfaces. A robot intended for disinfecting walls should be capable of following the wall concerned, while maintaining a given distance, to be effective. The ability to operate in an unknown environment while coping with uncertainties is crucial for a wall disinfection robot intended for deployment in public spaces. Therefore, this paper contributes to the state-of-the-art by proposing a novel method of establishing the wall-following behavior for a wall disinfection robot using fuzzy logic. A non-singleton Type 1 Fuzzy Logic System (T1-FLS) and a non-singleton Interval Type 2 Fuzzy Logic System (IT2-FLS) are developed in this regard. The wall-following behavior of the two fuzzy systems was evaluated through simulations by considering heterogeneous wall arrangements. The simulation results validate the real-world applicability of the proposed FLSs for establishing the wall-following behavior for a wall disinfection robot. Furthermore, the statistical outcomes show that the IT2-FLS has significantly superior performance than the T1-FLS in this application.