Design of sTetro: A Modular, Reconfigurable, and Autonomous Staircase Cleaning Robot

The mechanical, electrical, and autonomy aspects of designing a novel, modular, and reconfigurable cleaning robot, dubbed as sTetro (stair Tetro), are presented. The developed robotic platform uses a vertical conveyor mechanism to reconfigure itself and is capable of navigating over flat surfaces as well as staircases, thus significantly extending the automated cleaning capabilities as compared to conventional home cleaning robots. The mechanical design and system architecture are introduced first, followed by a detailed description of system modelling and controller design efforts in sTetro. An autonomy algorithm is also proposed for self-reconfiguration, locomotion, and autonomous navigation of sTetro in the controlled environment, for example, in homes/offices with a flat floor and a straight staircase. A staircase recognition algorithm is presented to distinguish between the surrounding environment and the stairs. The misalignment detection technique of the robot with a front staircase riser is also given, and a feedback from the IMU sensor for misalignment corrective measures is provided. The experiments performed with the sTetro robot demonstrated the efficacy and validity of the developed system models, control, and autonomy approaches.

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

Robotica ◽

10.1017/s0263574721000497 ◽

2021 ◽

pp. 1-26

Author(s):

Meng-Yuan Chen ◽

Yong-Jian Wu ◽

Hongmei He

Keyword(s):

Mobile Robot ◽

Navigation System ◽

Autonomous Navigation ◽

Clustering Algorithm ◽

Modular Design ◽

Optimal Path ◽

Surrounding Environment ◽

Computing Complexity ◽

The Arts ◽

Window Approach

Abstract 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.

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Computer Vision based Autonomous Navigation in Controlled Environment

10.1109/icrai54018.2021.9651414 ◽

2021 ◽

Author(s):

Sarmad Shafique ◽

Samia Abid ◽

Faisal Riaz ◽

Zainab Ejaz

Keyword(s):

Computer Vision ◽

Autonomous Navigation ◽

Controlled Environment

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Design and Experiment of a Novel Façade Cleaning Robot with a Biped Mechanism

Applied Sciences ◽

10.3390/app8122398 ◽

2018 ◽

Vol 8 (12) ◽

pp. 2398 ◽

Cited By ~ 3

Author(s):

Shunsuke Nansai ◽

Keichi Onodera ◽

Prabakaran Veerajagadheswar ◽

Mohan Rajesh Elara ◽

Masami Iwase

Keyword(s):

Polynomial Interpolation ◽

Area Coverage ◽

Glass Panel ◽

High Rise ◽

Cleaning Robot ◽

Glass Panels ◽

Glass Facade ◽

Cleaning Robots ◽

Real Scenario ◽

Glass Façade

Façade cleaning in high-rise buildings has always been considered a hazardous task when carried out by labor forces. Even though numerous studies have focused on the development of glass façade cleaning systems, the available technologies in this domain are limited and their performances are broadly affected by the frames that connect the glass panels. These frames generally act as a barrier for the glass façade cleaning robots to cross over from one glass panel to another, which leads to a performance degradation in terms of area coverage. We present a new class of façade cleaning robot with a biped mechanism that is able overcome these obstacles to maximize its area coverage. The developed robot uses active suction cups to adhere to glass walls and adopts mechanical linkage to navigate the glass surface to perform cleaning. This research addresses the design challenges in realizing the developed robot. Its control system consists of inverse kinematics, a fifth polynomial interpolation, and sequential control. Experiments were conducted in a real scenario, and the results indicate that the developed robot achieves significantly higher coverage performance by overcoming both negative and positive obstacles in a glass panel.

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Cascaded Machine-Learning Technique for Debris Classification in Floor-Cleaning Robot Application

Applied Sciences ◽

10.3390/app8122649 ◽

2018 ◽

Vol 8 (12) ◽

pp. 2649 ◽

Cited By ~ 14

Author(s):

Balakrishnan Ramalingam ◽

Anirudh Lakshmanan ◽

Muhammad Ilyas ◽

Anh Le ◽

Mohan Elara

Keyword(s):

Binary Classification ◽

Support Vector ◽

Single Shot ◽

Machine Learning Technique ◽

Cleaning Robot ◽

Svm Model ◽

Learning Technique ◽

Essential Function ◽

Cleaning Robots

Debris detection and classification is an essential function for autonomous floor-cleaning robots. It enables floor-cleaning robots to identify and avoid hard-to-clean debris, specifically large liquid spillage debris. This paper proposes a debris-detection and classification scheme for an autonomous floor-cleaning robot using a deep Convolutional Neural Network (CNN) and Support Vector Machine (SVM) cascaded technique. The SSD (Single-Shot MultiBox Detector) MobileNet CNN architecture is used for classifying the solid and liquid spill debris on the floor through the captured image. Then, the SVM model is employed for binary classification of liquid spillage regions based on size, which helps floor-cleaning devices to identify the larger liquid spillage debris regions, considered as hard-to-clean debris in this work. The experimental results prove that the proposed technique can efficiently detect and classify the debris on the floor and achieves 95.5% percent classification accuracy. The cascaded approach takes approximately 71 milliseconds for the entire process of debris detection and classification, which implies that the proposed technique is suitable for deploying in real-time selective floor-cleaning applications.

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Design of a Robotic Cannula for Robotic Lumber Discectomy

Volume 5A: 43rd Mechanisms and Robotics Conference ◽

10.1115/detc2019-97365 ◽

2019 ◽

Author(s):

Yang Ding ◽

Benjamin V. Johnson ◽

David J. Cappelleri

Keyword(s):

Controller Design ◽

Mechanical Design ◽

Lumbar Discectomy ◽

Surgical Instruments ◽

Herniated Disc ◽

Axial Position ◽

Robotic Approach ◽

Instrument Translation ◽

Gear Trains ◽

Fully Functioning

Abstract In this paper, the design of the robotic cannula for minimally invasive robotic lumbar discectomy is presented. Lumbar discectomy is the surgery to remove the herniated disc material that is pressing on a nerve root or spinal cord. Recently, a robotic approach to performing this procedure has been proposed that utilizes multiple teleoperated articulated instruments inserted into the surgical workspace using a single cannula. In this paper, we propose a new robotic cannula system to work in conjunction with this new procedure. It allows for the independent teleoperated control of the axial position and rotation of up to three surgical instruments at the same time. The mechanical design, controller design, and prototype of new system are presented in this paper demonstrating a fully functioning device for this application. A novel worm gear and rack system allow for the instrument translation while and embedded gear trains produce the rotational movement. Steady-state errors of less than 50 μm for translation and less than 2° for rotational motion are obtained.

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Multi-Sensor Orientation Tracking for a Façade-Cleaning Robot

Sensors ◽

10.3390/s20051483 ◽

2020 ◽

Vol 20 (5) ◽

pp. 1483 ◽

Cited By ~ 1

Author(s):

Manuel Vega-Heredia ◽

Ilyas Muhammad ◽

Sriharsha Ghanta ◽

Vengadesh Ayyalusami ◽

Siti Aisyah ◽

...

Keyword(s):

Orientation Angle ◽

Position Estimation ◽

Measurement Unit ◽

Vision Sensor ◽

Window Frame ◽

Cleaning Robot ◽

Heading Angle ◽

Glass Facade ◽

Cleaning Robots ◽

Glass Façade

Glass-façade-cleaning robots are an emerging class of service robots. This kind of cleaning robot is designed to operate on vertical surfaces, for which tracking the position and orientation becomes more challenging. In this article, we have presented a glass-façade-cleaning robot, Mantis v2, who can shift from one window panel to another like any other in the market. Due to the complexity of the panel shifting, we proposed and evaluated different methods for estimating its orientation using different kinds of sensors working together on the Robot Operating System (ROS). For this application, we used an onboard Inertial Measurement Unit (IMU), wheel encoders, a beacon-based system, Time-of-Flight (ToF) range sensors, and an external vision sensor (camera) for angular position estimation of the Mantis v2 robot. The external camera is used to monitor the robot’s operation and to track the coordinates of two colored markers attached along the longitudinal axis of the robot to estimate its orientation angle. ToF lidar sensors are attached on both sides of the robot to detect the window frame. ToF sensors are used for calculating the distance to the window frame; differences between beam readings are used to calculate the orientation angle of the robot. Differential drive wheel encoder data are used to estimate the robot’s heading angle on a 2D façade surface. An integrated heading angle estimation is also provided by using simple fusion techniques, i.e., a complementary filter (CF) and 1D Kalman filter (KF) utilizing the IMU sensor’s raw data. The heading angle information provided by different sensory systems is then evaluated in static and dynamic tests against an off-the-shelf attitude and heading reference system (AHRS). It is observed that ToF sensors work effectively from 0 to 30 degrees, beacons have a delay up to five seconds, and the odometry error increases according to the navigation distance due to slippage and/or sliding on the glass. Among all tested orientation sensors and methods, the vision sensor scheme proved to be better, with an orientation angle error of less than 0.8 degrees for this application. The experimental results demonstrate the efficacy of our proposed techniques in this orientation tracking, which has never applied in this specific application of cleaning robots.

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Landing Control of Foot with Springs for Walking Robots on Rough Terrain

International Journal of Advanced Robotic Systems ◽

10.5772/7238 ◽

2009 ◽

Vol 6 (3) ◽

pp. 25 ◽

Cited By ~ 3

Author(s):

Moyuru Yamada ◽

Shigenori Sano ◽

Naoki Uchiyama

Keyword(s):

Controller Design ◽

Impact Force ◽

Reaction Force ◽

Walking Robots ◽

Flat Surfaces ◽

Uneven Terrain ◽

Biped Walking Robot ◽

Foot Position ◽

The Impact ◽

Landing Control

Landing control is one of the important issues for biped walking robot, because robots are expected to walk on not only known flat surfaces but also unknown and uneven terrain for working at various fields. This paper presents a new controller design for a robotic foot to land on unknown terrain. The robotic foot considered in this study equips springs to reduce the impact force at the foot landing. There are two objectives in the landing control; achieving the desired ground reaction force and positioning the foot on unknown terrain. To achieve these two objectives simultaneously by adjusting the foot position, we propose a PI force controller with a desired foot position, which guarantees the robust stability of control system with respect to terrain variance, and exact positioning of the foot to unknown terrain. Simulation results using the Open Dynamics Engine demonstrate the effectiveness of the proposed controller.

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Dynamics and Controller Design of a Screw Wheel Drive Holonomic Rescue Robot

Volume 4: Dynamics, Control and Uncertainty, Parts A and B ◽

10.1115/imece2012-85730 ◽

2012 ◽

Author(s):

Emin Faruk Kececi

Keyword(s):

Adaptive Control ◽

Control Algorithm ◽

Controller Design ◽

Mechanical Design ◽

Future Research ◽

Rescue Robot ◽

Wheel Drive ◽

The Stability ◽

Adaptive Control Algorithm ◽

Future Work

This paper reports a holonomic rescue robot where the robot is driven by screw wheels. The necessity of a such platform is explained and the mechanical design and the actual prototype are presented. In order to design an adaptive control algorithm to ensure the trajectory tracking, the dynamical model is constructed. The stability of the adaptive control algorithm is proven with Lyapunov stability analysis. The necessary electronics to implement the controller algorithm is explained and the conclusions and future work section reports the results of the study as well as the future research directions.

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An Ear Wearable Device System for Facial Emotion Recognition Disorders

Frontiers in Bioengineering and Biotechnology ◽

10.3389/fbioe.2021.703048 ◽

2021 ◽

Vol 9 ◽

Author(s):

Zhengxu Lian ◽

Yingjie Guo ◽

Xinyu Cao ◽

Wendi Li

Keyword(s):

Emotion Recognition ◽

Data Storage ◽

Mobile Terminal ◽

Recognition Algorithm ◽

Facial Emotion Recognition ◽

Wearable Device ◽

Facial Emotion ◽

Data Sets ◽

Physiological Signal ◽

Surrounding Environment

A wearable device system was proposed in the present work to address the problem of facial emotion recognition disorders. The proposed system could comprehensively analyze the user’s own stress status, emotions of people around, and the surrounding environment. The system consists of a multi-dimensional physiological signals acquisition module, an image acquisition and transmission module, a user interface of the user mobile terminal, and a cloud database for data storage. Moreover, a deep learning based multi-model physiological signal pressure recognition algorithm and a facial emotion recognition algorithm were designed and implemented in the system. Some publicly available data sets were used to test the two algorithms, and the experiment results showed that the two algorithms could well realize the expected functions of the system.

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Design of a Reconfigurable Wall Disinfection Robot

Sensors ◽

10.3390/s21186096 ◽

2021 ◽

Vol 21 (18) ◽

pp. 6096

Author(s):

Ash Wan Yaw Sang ◽

Chee Gen Moo ◽

S. M. Bhagya P. Samarakoon ◽

M. A. Viraj J. Muthugala ◽

Mohan Rajesh Elara

Keyword(s):

Public Spaces ◽

Test Cases ◽

Cleaning Robot ◽

Risk Areas ◽

Cleaning Robots ◽

Cleaning And Disinfection ◽

Indoor Spaces ◽

Wall Following ◽

Logic System ◽

Robot Platform

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.

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