Electric Vehicle Automation through a Distributed Control System for Search and Rescue Operations

Cruz-Ramos, Marco Polo; Hassard, Christian; Gordillo, José Luís

doi:10.1007/978-3-642-37807-2_22

Cited by 5 publications

(3 citation statements)

References 10 publications

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“…For example, the authors of [91] propose and deploy an electric vehicle which they use to carry and deploy smaller search robots automatically for search and rescue operations. They propose using a Distributed Control System (DCS) which is able to create three closed loop control systems that controls the steering, speed, and deployment mechanism for the vehicle.…”

Section: Path Planningmentioning

confidence: 99%

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The integration of mobile (tele) robotics and wireless sensor networks: A survey

Wichmann

Okkalıoğlu

Korkmaz

2014

Computer Communications

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Section: Path Planningmentioning

confidence: 99%

“…A teleoperated robot to deploy wireless sensors [89,90,91]. Autonomous robots and SLAM to localize and map the sensed area [12].…”

Section: Deploymentmentioning

confidence: 99%

The integration of mobile (tele) robotics and wireless sensor networks: A survey

Wichmann

Okkalıoğlu

Korkmaz

2014

Computer Communications

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“…), upon the detection of the problems (e.g., smoke is detected in some areas of the building), a robot is expected to react immediately and resolve the issue. Robots are beneficial in scenarios where human participation is dangerous or not possible (e.g., rescue activities after natural disasters [2]). One of the main problems in the wireless sensor and robot networks is how and to which robot(s) to allocate the task.…”

Section: Introductionmentioning

confidence: 99%

Routing with Face Traversal and Auctions Algorithms for Task Allocation in WSRN

Stanulovic

Mitton

Mezei

2021

Sensors

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Four new algorithms (RFTA1, RFTA2, GFGF2A, and RFTA2GE) handling the event in wireless sensor and robot networks based on the greedy-face-greedy (GFG) routing extended with auctions are proposed in this paper. In this paper, we assume that all robots are mobile, and after the event is found (reported by sensors), the goal is to allocate the task to the most suitable robot to act upon the event, using either distance or the robots' remaining energy as metrics. The proposed algorithms consist of two phases. The first phase of algorithms is based on face routing, and we introduced the parameter called search radius (SR) at the end of this first phase. Routing is considered successful if the found robot is inside SR. After that, the second phase, based on auctions, is initiated by the robot found in SR trying to find a more suitable one. In the simulations, network lifetime and communication costs are measured and used for comparison. We compare our algorithms with similar algorithms from the literature (k-SAAP and BFS) used for the task assignment. RFTA2 and RFTA2GE feature up to a seven-times-longer network lifetime with significant communication overhead reduction compared to k-SAAP and BFS. Among our algorithms, RFTA2GE features the best robot energy utilization.

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Minimum hop and/or minimum distance robot movement with connectivity constraints in WSRNs

Wichmann

Korkmaz

Tosun

2014

2014 IEEE Global Communications Conference

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Electric Vehicle Automation through a Distributed Control System for Search and Rescue Operations

Cited by 5 publications

References 10 publications

The integration of mobile (tele) robotics and wireless sensor networks: A survey

The integration of mobile (tele) robotics and wireless sensor networks: A survey

Routing with Face Traversal and Auctions Algorithms for Task Allocation in WSRN

Minimum hop and/or minimum distance robot movement with connectivity constraints in WSRNs

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