scholarly journals Tackling Area Coverage Problems in a Reconfigurable Floor Cleaning Robot Based on Polyomino Tiling Theory

2018 ◽  
Vol 8 (3) ◽  
pp. 342 ◽  
Author(s):  
Veerajagadheswar Prabakaran ◽  
Rajesh Mohan ◽  
Vinu Sivanantham ◽  
Thejus Pathmakumar ◽  
Suganya Kumar
Keyword(s):  
Area Coverage ◽  
Cleaning Robot ◽  
Coverage Problems

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

2018 ◽  
Vol 8 (12) ◽  
pp. 2398 ◽  
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.

scholarly journals Tradeoff Between Area Coverage and Energy Usage of a Self-Reconfigurable Floor Cleaning Robot Based on User Preference

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 76267-76275 ◽  
Author(s):  
M. A. Viraj J. Muthugala ◽  
S. M. Bhagya P. Samarakoon ◽  
Mohan Rajesh Elara
Keyword(s):  
Area Coverage ◽  
User Preference ◽  
Energy Usage ◽  
Cleaning Robot

Non-Autonomous Feedback Control for Area Coverage Problems With Time-Varying Risk

2016 ◽  
Author(s):  
Suruz Miah ◽  
Mostafa M. H. Fallah ◽  
Arian Y. Panah ◽  
Davide Spinello
Keyword(s):  
Mobile Agents ◽  
Optimization Problems ◽  
Area Coverage ◽  
Control Law ◽  
Time Varying ◽  
External Threats ◽  
Barbalat’S Lemma ◽  
Diffusion Mechanisms ◽  
Area Surveillance ◽  
Coverage Problems

Motivated by area coverage optimization problems with time varying risk densities, we propose a decentralized control law for a team of autonomous mobile agents in a two dimensional area such that their asymptotic configurations optimize a generalized non-autonomous coverage metric. The generalized non-autonomous coverage metric explicitly depends on a nonuniform time-varying measurable scalar field that is not directly controllable by agents. Several interesting scenarios emerge with time varying risk density. In this work, we consider the case of area surveillance against moving targets or external threats penetrating through the perimeter, and the case of environmental monitoring and intervention with deployment of mobile sensors in areas affected by penetration of substances governed by diffusion mechanisms, as for example oil in a marine environment. In the presence of time-varying risk density the coverage metric is non-autonomous as it includes a time varying component that does not depend on the evolution of the agents. Our non-autonomous feedback law accounts for the time-varying component through a term that vanishes when the risk eventually stops evolving. Optimality with respect to the induced non-autonomous coverage is proven in the framework of Barbalat’s lemma, and the performance is illustrated through simulation of the these two scenarios.

scholarly journals Reinforcement Learning-Based Complete Area Coverage Path Planning for a Modified hTrihex Robot

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1067 ◽  
Author(s):  
Koppaka Ganesh Sai Apuroop ◽  
Anh Vu Le ◽  
Mohan Rajesh Elara ◽  
Bing J. Sheu
Keyword(s):  
Reinforcement Learning ◽  
Short Term Memory ◽  
Learning Algorithm ◽  
Area Coverage ◽  
Current Paper ◽  
Coverage Problem ◽  
Entire Area ◽  
Maximum Area ◽  
Coverage Path Planning ◽  
Cleaning Robot

One of the essential attributes of a cleaning robot is to achieve complete area coverage. Current commercial indoor cleaning robots have fixed morphology and are restricted to clean only specific areas in a house. The results of maximum area coverage are sub-optimal in this case. Tiling robots are innovative solutions for such a coverage problem. These new kinds of robots can be deployed in the cases of cleaning, painting, maintenance, and inspection, which require complete area coverage. Tiling robots’ objective is to cover the entire area by reconfiguring to different shapes as per the area requirements. In this context, it is vital to have a framework that enables the robot to maximize the area coverage while minimizing energy consumption. That means it is necessary for the robot to cover the maximum area with the least number of shape reconfigurations possible. The current paper proposes a complete area coverage planning module for the modified hTrihex, a honeycomb-shaped tiling robot, based on the deep reinforcement learning technique. This framework simultaneously generates the tiling shapes and the trajectory with minimum overall cost. In this regard, a convolutional neural network (CNN) with long short term memory (LSTM) layer was trained using the actor-critic experience replay (ACER) reinforcement learning algorithm. The simulation results obtained from the current implementation were compared against the results that were generated through traditional tiling theory models that included zigzag, spiral, and greedy search schemes. The model presented in the current paper was also compared against other methods where this problem was considered as a traveling salesman problem (TSP) solved through genetic algorithm (GA) and ant colony optimization (ACO) approaches. Our proposed scheme generates a path with a minimized cost at a lesser time.

A Bipopulation-Based Evolutionary Algorithm for Solving Full Area Coverage Problems

2013 ◽  
Vol 13 (12) ◽  
pp. 4796-4807 ◽  
Author(s):  
Joon-Hong Seok ◽  
Joon-Yong Lee ◽  
Won Kim ◽  
Ju-Jang Lee
Keyword(s):  
Evolutionary Algorithm ◽  
Area Coverage ◽  
Coverage Problems

Generalized non-autonomous metric optimization for area coverage problems with mobile autonomous agents

Automatica ◽  
2017 ◽  
Vol 80 ◽  
pp. 295-299 ◽  
Author(s):  
Suruz Miah ◽  
Arian Y. Panah ◽  
Mostafa Mohammad Hossein Fallah ◽  
Davide Spinello
Keyword(s):  
Autonomous Agents ◽  
Area Coverage ◽  
Coverage Problems
Sign in / Sign up

Export Citation Format

Share Document