Towards solving the mobility issues of unmanned ground vehicles

Odedra, Siddharth; Prior, Stephen D.; Karamanoglu, Mehmet

doi:10.1117/12.721495

Cited by 4 publications

(5 citation statements)

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“…The operator indicates the subtraction of two TSP paths. For example, Path1 = {1,2,3,4} and Path2 = {1,2,4,3}, Path1 Path2 = SO (3,4). In contrast with Formula (18), r ind in Formula ( 22) denotes the probability that all of the swap operators in the swap sequence (pbest id − x k id ) are used, and r gol denotes the probability that all the swap operators in the swap sequence (gbest d − x k id ) are used.…”

Section: Swap Sequence-based Psomentioning

confidence: 99%

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A Multigoal Path-Planning Approach for Explosive Ordnance Disposal Robots Based on Bidirectional Dynamic Weighted-A* and Learn Memory-Swap Sequence PSO Algorithm

Qiao

Jiang

2023

Symmetry

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In order to protect people’s lives and property, increasing numbers of explosive disposal robots have been developed. It is necessary for an explosive ordinance disposal (EOD) robot to quickly detect all explosives, especially when the location of the explosives is unknown. To achieve this goal, we propose a bidirectional dynamic weighted-A star (BD-A*) algorithm and a learn memory-swap sequence particle swarm optimization (LM-SSPSO) algorithm. Firstly, in the BD-A* algorithm, our aim is to obtain the shortest distance path between any two goal positions, considering computation time optimization. We optimize the computation time by introducing a bidirectional search and a dynamic OpenList cost weight strategy. Secondly, the search-adjacent nodes are extended to obtain a shorter path. Thirdly, by using the LM-SSPSO algorithm, we aim to plan the shortest distance path that traverses all goal positions. The problem is similar to the symmetric traveling salesman problem (TSP). We introduce the swap sequence strategy into the traditional PSO and optimize the whole PSO process by imitating human learning and memory behaviors. Fourthly, to verify the performance of the proposed algorithm, we begin by comparing the improved A* with traditional A* over different resolutions, weight coefficients, and nodes. The hybrid PSO algorithm is also compared with other intelligent algorithms. Finally, different environment maps are also discussed to further verify the performance of the algorithm. The simulation results demonstrate that our improved A* algorithm has superior performance by finding the shortest distance with less computational time. In the simulation results for LM-SSPSO, the convergence rate significantly improves, and the improved algorithm is more likely to obtain the optimal path.

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Section: Swap Sequence-based Psomentioning

confidence: 99%

“…Many countries have developed different kinds of EOD robots. For example, the British Morfax corporation has invented an EOD robot called Wheelbarrow [4]. It is one of the most famous EOD robots in the world, possessing good vehicle mobility and explosive disposal performance.…”

Section: Introductionmentioning

confidence: 99%

A Multigoal Path-Planning Approach for Explosive Ordnance Disposal Robots Based on Bidirectional Dynamic Weighted-A* and Learn Memory-Swap Sequence PSO Algorithm

Qiao

Jiang

2023

Symmetry

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“…This is because the crawler vehicles tend to tumble when they go over a high step, as shown in Figure (a) and described in detail in Section . To improve terrain adaptability on extremely rough terrain, variable/multiple crawlers have been introduced in the previous works (Odedra et al., ). Nevertheless, with active variable/multiple crawler mechanisms, there is often a tradeoff with the performance due to the increase in the number of actuators and the complexity of the mechanism.…”

Section: Blade‐type Crawler Vehiclementioning

confidence: 99%

Development of a Blade‐type Crawler Mechanism for a Fast Deployment Task to Observe Eruptions on Mt. Mihara

Yamada

Miyagawa

Yokoto

et al. 2015

Journal of Field Robotics

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Observing a crater during a volcanic eruption is a dangerous task that is still being performed by volcanologists. Because of the risks involved, it is proposed that this observation be performed by robots rather than humans. Unlike rescue robots that operate inside buildings, those that observe craters during volcanic activities are expected to demonstrate rapid movements because the environmental conditions during an eruption can change in a split second. Furthermore, the cost of the robots to be developed should be kept to a minimum, as there is a high chance that they will be damaged or lost. This study proposes a blade‐type crawler vehicle with improved performance over rough terrain. The vehicle does not compromise speed nor does it have complex controls, which keeps the cost low. The objective of the study was to observe eruptions on Mt. Mihara on Izu Oshima Island, where there have been threats of eruption in recent years. The proposed vehicle was tested, and its effectiveness was demonstrated through laboratory experiments and a field test on Mt. Mihara. This vehicle was capable of traveling on scoria desert and vulnerable, uneven, and rough terrain, including bushes, on Izu Oshima Island. In addition, the vehicle recorded a maximum velocity of about 10 km/h and climbed over steps with a height of about 135 mm, which is about 270% of the diameter of its wheel. Moreover, it is small, lightweight (2.5 kg), and it can be operated by one person. Through practical experiments, it was verified that the vehicle demonstrated superior performance and speed over rough terrain as compared with other crawler mechanisms. Therefore, it was found that the mechanism was effective for an unmanned probe device, especially in a hypothetical volcanic eruption site on Izu Oshima Island.

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“…In order to improve the rough terrain drivability with small size, it is necessary not only to simply miniature analogously but also to inspire from the wharf roach, which has high mobility despite of small size. 1 …”

Section: Introductionmentioning

confidence: 97%

“…These robots are used instead of people to carry out data collection and other operations in locations that are dangerous or difficult for people to enter [1]. These robots must perform over rough terrain, have the ability to move in multiple directions, have speed, a simple mechanism, and should be easy to control.…”

Section: Introductionmentioning

confidence: 99%

Blade-type crawler vehicle bio-inspired by a wharf roach

Yamada

Endo

Fukushima

2014

2014 IEEE International Conference on Robotics and Automation (ICRA)

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Unmanned rescue, observation and/or research vehicles with high terrain adaptability, fast velocity and high reliability to reach difficult rough terrain locations are still demanded, but most vehicles increase rough terrain adapt ability at the expense of low velocity and/or complex mechanisms. We propose a novel vehicle consisting of a very simple blade-type crawler and active antennas with rollers, resembling a wharf roach. This configuration assures stable travelling over uneven terrain at high-speeds, with a very simple and reliable mechanism. This article presents the basic concept, mechanical design of the crawler and the antennas, and the basic motion control strategies. Moreover, we built and tested the first small mechanical prototype named KEIOS-I, and got successful results from experiments on uneven terrain at a high-speed traveling, and also lateral travelling and jumping motions. Future work will also implement roller skating mode using the active antennas equipped with rollers.

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Towards solving the mobility issues of unmanned ground vehicles

Cited by 4 publications

References 0 publications

A Multigoal Path-Planning Approach for Explosive Ordnance Disposal Robots Based on Bidirectional Dynamic Weighted-A* and Learn Memory-Swap Sequence PSO Algorithm

A Multigoal Path-Planning Approach for Explosive Ordnance Disposal Robots Based on Bidirectional Dynamic Weighted-A* and Learn Memory-Swap Sequence PSO Algorithm

Development of a Blade‐type Crawler Mechanism for a Fast Deployment Task to Observe Eruptions on Mt. Mihara

Blade-type crawler vehicle bio-inspired by a wharf roach

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