Radio Controlled Beach Cleaning Bot

Bano, Nasreen; Amin, Amina; Boghani, Hussain; Tariq, Hiba; Bakhtawar, Saba; Waggan, Illyas; Younas, Tanzila

doi:10.1109/icetas48360.2019.9117269

Cited by 8 publications

(3 citation statements)

References 7 publications

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“…The application of autonomous robotics in beach cleaning represents a developing area of research, still in its early stages but showing significant potential for advancement [10,11]. Traditional beach-cleaning robots, which are predominantly large-scale [12], often require human supervision and/or control, limiting their autonomy and operational efficiency [13][14][15]. However, recent advancements in DRL and simulation technologies have introduced new opportunities for improving these systems.…”

Section: State Of Artmentioning

confidence: 99%

RL-Based Sim2Real Enhancements for Autonomous Beach-Cleaning Agents

Quiroga,

Hermosilla,

Varas

et al. 2024

Applied Sciences

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This paper explores the application of Deep Reinforcement Learning (DRL) and Sim2Real strategies to enhance the autonomy of beach-cleaning robots. Experiments demonstrate that DRL agents, initially refined in simulations, effectively transfer their navigation skills to real-world scenarios, achieving precise and efficient operation in complex natural environments. This method provides a scalable and effective solution for beach conservation, establishing a significant precedent for the use of autonomous robots in environmental management. The key advancements include the ability of robots to adhere to predefined routes and dynamically avoid obstacles. Additionally, a newly developed platform validates the Sim2Real strategy, proving its capability to bridge the gap between simulated training and practical application, thus offering a robust methodology for addressing real-life environmental challenges.

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Section: State Of Artmentioning

confidence: 99%

RL-Based Sim2Real Enhancements for Autonomous Beach-Cleaning Agents

Quiroga,

Hermosilla,

Varas

et al. 2024

Applied Sciences

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show abstract

“…Nasreen Bano et al designed and built a prototype of a remote-controlled beach-cleaning robot, which includes a filtration mechanism and a drive mechanism. The robot's movement is remotely controlled through a Bluetooth module, and a vibration mechanism is used to separate sand from small debris, such as plastic fragments, glass shards, cans, and cigarette butts [36]. Tomoyasu Ichimura et al developed a small beach-cleaning robot called Hirottaro, which mimics the use of a broom and dustpan to clean the floor.…”

Section: Beach-garbage-cleaning Robotmentioning

confidence: 99%

A Spiral-Propulsion Amphibious Intelligent Robot for Land Garbage Cleaning and Sea Garbage Cleaning

Zhang

Huang

Chen

et al. 2023

JMSE

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To address the issue of current garbage cleanup vessels being limited to performing garbage cleaning operations in the ocean, without the capability of transferring the garbage from the ocean to the land, this paper presents a spiral-propulsion amphibious intelligent robot for land garbage cleaning and sea garbage cleaning. The design solution is as follows. A mechanical structure based on a spiral drum is proposed. The interior of the spiral drum is hollow, providing buoyancy, allowing the robot to travel both on marshy, tidal flats and on the water surface, in conjunction with underwater thrusters. Additionally, a mechanical-arm shovel is designed, which achieves two-degrees-of-freedom movement through a spiral spline guide and servo, facilitating garbage collection. Our experimental results demonstrated that the robot exhibits excellent maneuverability in marine environments and on beach, marsh, and tidal flat areas, and that it collects garbage effectively.

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“…(Degree of Freedom) robotic arm was used to pick up the trash from the grass. In [22], the robot was controlled remotely via radio signals, while dragging a mechanism which continuously ploughed and sieved the sand to remove the solid particles and store them in a bin. In [20], a pre-existing Care-O-Bot platform was used for the robot to explore the area, detect dirt, clear trash cans, and vacuum as it contained the required features like a seven-d.o.f.…”

Section: Comparative Studymentioning

confidence: 99%

OATCR: Outdoor Autonomous Trash-Collecting Robot Design Using YOLOv4-Tiny

et al. 2021

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This paper proposed an innovative mechanical design using the Rocker-bogie mechanism for resilient Trash-Collecting Robots. Mask-RCNN, YOLOV4, and YOLOv4-tiny were experimented on and analyzed for trash detection. The Trash-Collecting Robot was developed to be completely autonomous as it was able to detect trash, move towards it, and pick it up while avoiding any obstacles along the way. Sensors including a camera, ultrasonic sensor, and GPS module played an imperative role in automation. The brain of the Robot, namely, Raspberry Pi and Arduino, processed the data from the sensors and performed path-planning and consequent motion of the robot through actuation of motors. Three models for object detection were tested for potential use in the robot: Mask-RCNN, YOLOv4, and YOLOv4-tiny. Mask-RCNN achieved an average precision (mAP) of over 83% and detection time (DT) of 3973.29 ms, YOLOv4 achieved 97.1% (mAP) and 32.76 DT, and YOLOv4-tiny achieved 95.2% and 5.21 ms DT. The YOLOv4-tiny was selected as it offered a very similar mAP to YOLOv4, but with a much lower DT. The design was simulated on different terrains and behaved as expected.

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Radio Controlled Beach Cleaning Bot

Cited by 8 publications

References 7 publications

RL-Based Sim2Real Enhancements for Autonomous Beach-Cleaning Agents

RL-Based Sim2Real Enhancements for Autonomous Beach-Cleaning Agents

A Spiral-Propulsion Amphibious Intelligent Robot for Land Garbage Cleaning and Sea Garbage Cleaning

OATCR: Outdoor Autonomous Trash-Collecting Robot Design Using YOLOv4-Tiny

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