Path planning algorithm development for autonomous vacuum cleaner robots

Hasan, Kamrul; Nahid, Abdullah-Al; Reza, Khondker Jahid

doi:10.1109/iciev.2014.6850799

Cited by 61 publications

(26 citation statements)

References 5 publications

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“…Collision occurs when the sensors fail to detect objects (cross-talk, absorption, refraction, reflection, etc.). Bumpers are adapted to indoor motion as suggested in [72] and do not work in mud, sand, and gravel; we prefer IMU information, which does not interfere with the composition of the environment. Moreover, the dynamic model of the rover is not available, and we prefer to use an IMU sensor.…”

Section: Cnn For States Differentiationmentioning

confidence: 99%

Toward a robot swarm protecting a group of migrants

Vaidis

Otis

2020

Intel Serv Robotics

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Different geopolitical conflicts of recent years have led to mass migration of several civilian populations. These migrations take place in militarized zones, indicating real danger contexts for the populations. Indeed, civilians are increasingly targeted during military assaults. Defense and security needs have increased; therefore, there is a need to prioritize the protection of migrants. Very few or no arrangements are available to manage the scale of displacement and the protection of civilians during migration. In order to increase their security during mass migration in an inhospitable territory, this article proposes an assistive system using a team of mobile robots, labeled a rover swarm that is able to provide safety area around the migrants. We suggest a coordination algorithm including CNN and fuzzy logic that allows the swarm to synchronize their movements and provide better sensor coverage of the environment. Implementation is carried out using on a reduced scale rover to enable evaluation of the functionalities of the suggested software architecture and algorithms. Results bring new perspectives to helping and protecting migrants with a swarm that evolves in a complex and dynamic environment.

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Section: Cnn For States Differentiationmentioning

confidence: 99%

Toward a robot swarm protecting a group of migrants

Vaidis

Otis

2020

Intel Serv Robotics

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“…With the installation of these sensors on vacuum cleaning robots, corresponding path planning algorithms should be developed to complete the designated tasks. The path planning algorithms should be sophisticated to make educated assumptions about the operating environment and be able to react to a dynamic indoor environment [5]. Both the accuracy of the sensor modules and the intelligence of the path planning strategies determine the overall efficacy of the robots [6,7].…”

Section: Introductionmentioning

confidence: 99%

Realization Energy Optimization of Complete Path Planning in Differential Drive Based Self-Reconfigurable Floor Cleaning Robot

Tun

et al. 2019

Energies

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The efficiency of energy usage applied to robots that implement autonomous duties such as floor cleaning depends crucially on the adopted path planning strategies. Energy-aware for complete coverage path planning (CCPP) in the reconfigurable robots raises interesting research, since the ability to change the robot’s shape needs the dynamic estimate energy model. In this paper, a CCPP for a predefined workspace by a new floor cleaning platform (hTetro) which can self-reconfigure among seven tetromino shape by the cooperation of hinge-based four blocks with independent differential drive modules is proposed. To this end, the energy consumption is represented by travel distances which consider operations of differential drive modules of the hTetro kinematic designs to fulfill the transformation, orientation correction and translation actions during robot navigation processes from source waypoint to destination waypoint. The optimal trajectory connecting all pairs of waypoints on the workspace is modeled and solved by evolutionary algorithms of TSP such as Genetic Algorithm (GA) and Ant Optimization Colony (AC) which are among the well-known optimization approaches of TSP. The evaluations across several conventional complete coverage algorithms to prove that TSP-based proposed method is a practical energy-aware navigation sequencing strategy that can be implemented to our hTetro robot in different real-time workspaces. Moreover, The CCPP framework with its modulation in this paper allows the convenient implementation on other polynomial-based reconfigurable robots.

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“…Artificial Intelligence and path planning have fully assisted in the utilization of several robotic applications like vacuum cleaner [1], underwater [2], aerial vehicles [3] and blind people [4]. In motion planning, the principle issue is to compute the path which allows movement from any starting point to reach a goal point within the place while avoiding obstacles.…”

Section: Introductionmentioning

confidence: 99%

A Novel Path Planning System for Guidance of Blind People using Integration of GA and A* Techniques

Mohamed¹,

E.²,

F.³

2019

IJCA

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It is a challenging task for the blind people to perceive indoor environment information and walk independently. Path planning is a crucial requirement to provide constant assistance for blind people to navigate from one location to another. This paper presents a novel system for path planning to assist blind people for walking through the indoor environment and avoiding the obstacles. The algorithm is based on genetic algorithm and A* algorithm to select the shortest path that achieves the lowest computational time. A comparison a mong the GA, A* and the new algorithm shows that is faster and shorter than the previous algorithms.

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Path planning algorithm development for autonomous vacuum cleaner robots

Cited by 61 publications

References 5 publications

Toward a robot swarm protecting a group of migrants

Toward a robot swarm protecting a group of migrants

Realization Energy Optimization of Complete Path Planning in Differential Drive Based Self-Reconfigurable Floor Cleaning Robot

A Novel Path Planning System for Guidance of Blind People using Integration of GA and A* Techniques

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