Autonomous Rover Navigation Using GPS Based Path Planning

Arabi, Abul Al; Sakib, Hasib Ul; Sarkar, Pranabesh; Proma, Tanjina Piash; Anowar, Jahedul; Amin, M. Ashraful

doi:10.1109/ams.2017.22

Cited by 9 publications

(5 citation statements)

References 10 publications

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“…Some other works have used control strategies such as sliding modes, PID or the properties of a kinematic model [8][9][10]. Competitions like the ERC, IRC, CIRC and URC test rovers at the expense of adopting their qualities for planetary exploration vehicles; for such events, works like those of Arabi et al [11] and Polash et al [12] opted for trajectory tracking strategies to pass the autonomous navigation tests.…”

Section: Introductionmentioning

confidence: 99%

Simplified Strategy for Trajectory Tracking Application of a Passive Suspension Rover-Type Mobile Robot

Diaz-Ortega,

Gutiérrez-Frías,

Aguirre-Anaya

et al. 2024

Machines

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In the present work, based on an approximate modelling of a rover-type robot and a proportional control law, a simplified trajectory tracking strategy for a passive suspension rover-type mobile robot was developed. This strategy achieves trajectory tracking and the autonomous displacement of a rover, of which its configuration involves complex kinematics and dynamics. All these lineaments reduce the complexity of the analysis, the number of electronic components to implement, the computational requirements and the energy consumption. The robotic system used is based on the Shrimp rover, which is a robot with a passive suspension that is capable of carrying out displacements over rough terrain. The tests were performed using numerical simulations with different desired trajectories, and also using experimental tests using a passive suspension rover-type mobile robot.

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Section: Introductionmentioning

confidence: 99%

Simplified Strategy for Trajectory Tracking Application of a Passive Suspension Rover-Type Mobile Robot

Diaz-Ortega,

Gutiérrez-Frías,

Aguirre-Anaya

et al. 2024

Machines

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“…The Japan Aerospace eXploration Agency (JAXA) has introduced a path-planning algorithm [5] that prioritizes decision-making considering the limitations of sunlight rather than simply avoiding obstacles. GPS-based path planning algorithm [6] is proposed for rovers to generate paths in difficult terrain. However, a mature positioning system for lunar environments has yet to be developed.…”

Section: Introductionmentioning

confidence: 99%

Lunar Rover Collaborated Path Planning with Artificial Potential Field-Based Heuristic on Deep Reinforcement Learning

Lu,

Xu,

et al. 2024

Aerospace

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The International Lunar Research Station, to be established around 2030, will equip lunar rovers with robotic arms as constructors. Construction requires lunar soil and lunar rovers, for which rovers must go toward different waypoints without encountering obstacles in a limited time due to the short day, especially near the south pole. Traditional planning methods, such as uploading instructions from the ground, can hardly handle many rovers moving on the moon simultaneously with high efficiency. Therefore, we propose a new collaborative path-planning method based on deep reinforcement learning, where the heuristics are demonstrated by both the target and the obstacles in the artificial potential field. Environments have been randomly generated where small and large obstacles and different waypoints are created to collect resources, train the deep reinforcement learning agent to propose actions, and lead the rovers to move without obstacles, finish rovers’ tasks, and reach different targets. The artificial potential field created by obstacles and other rovers in every step affects the action choice of the rover. Information from the artificial potential field would be transformed into rewards in deep reinforcement learning that helps keep distance and safety. Experiments demonstrate that our method can guide rovers moving more safely without turning into nearby large obstacles or collision with other rovers as well as consuming less energy compared with the multi-agent A-Star path-planning algorithm with improved obstacle avoidance method.

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“…Navigation frameworks find their application in autonomous delivery carts, rovers, and daily use household gadgets such as vacuum bots [3], [9]- [11]. Depending on the application, different navigation systems have been used in robotics [12]- [17]. Navigation systems used for rovers are mainly of the following types  Navigation using IMU  GPS-based system of navigation  GPS and inertial sensors system Navigation systems are utilized for robots according to the requirement and purposes such as remote exploration and delivery of products using small carts ranging from indoor to outdoor navigation.…”

Section: Introductionmentioning

confidence: 99%

“…Navigation systems used for rovers are mainly of the following types  Navigation using IMU  GPS-based system of navigation  GPS and inertial sensors system Navigation systems are utilized for robots according to the requirement and purposes such as remote exploration and delivery of products using small carts ranging from indoor to outdoor navigation. For indoor purposes, inertial sensors are used in navigation and for outdoor purposes, GPS based navigation system is used along with other sensors(Compass, accelerometer) [12], [18]. Depending upon these indoor/outdoor navigation requirements and environment, rover chassis and sensors are developed to make the robot more autonomous and robust.…”

Section: Introductionmentioning

confidence: 99%

“…Different outdoor navigation systems have been developed and applied over years to achieve the target/goal. In the study [12], system was developed which uses GPS to navigate through the path. Still, the algorithm corrects the direction of motion using the distance, which leaves many uncertainties unaddressed as the PID controller will need some time and will have to move in all directions to understand the direction in which distance to the target will decrease.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

IMU Aided GPS Based Navigation of Ackermann Steered Rover

Arshad

Hussain

Maud

et al. 2022

IJIST

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GPS signal loss is a major issue when the navigation system of rovers is based solely on GPS for outdoor navigation rendering the rover stuck in the mid of the road in case of signal loss. In this study, a low-cost IMU aided GPS-based navigation system for Ackermann Steered mobile robots is presented and tested to cater to the issue of GPS signal loss along. GPS path is selected and fed using the android application which provides real-time location tracking of the rover on the map embedded into the application. System utilizes Arduino along with the node MCU, compass, IMU, Rotary encoders, and an Ackermann steered rover. Controller processes the path file, compares its current position with the path coordinates and navigates using inertial sensor aided navigation algorithm, avoiding obstacles to reach its destination. IMU measures the distance traveled from each path point, and in case of signal loss, it makes the rover move for the remaining distance in the direction of destination point. Rover faced a sinusoidal motion due to the steering, so PID was implemented. The system was successfully tested on the IST premises and finds its application in the delivery trolley, institutional delivery carts, and related applications.

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Autonomous Rover Navigation Using GPS Based Path Planning

Cited by 9 publications

References 10 publications

Simplified Strategy for Trajectory Tracking Application of a Passive Suspension Rover-Type Mobile Robot

Simplified Strategy for Trajectory Tracking Application of a Passive Suspension Rover-Type Mobile Robot

Lunar Rover Collaborated Path Planning with Artificial Potential Field-Based Heuristic on Deep Reinforcement Learning

IMU Aided GPS Based Navigation of Ackermann Steered Rover

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