Yogang Singh

Bio: Yogang Singh is an academic researcher from University of Plymouth. The author has contributed to research in topics: Motion planning & Underwater glider. The author has an hindex of 10, co-authored 22 publications receiving 291 citations. Previous affiliations of Yogang Singh include Purdue University & Indian Institute of Technology Madras.

A Novel Double Layered Hybrid Multi-Robot Framework for Guidance and Navigation of Unmanned Surface Vehicles in a Practical Maritime Environment

Abstract: Formation control and cooperative motion planning are two major research areas currently being used in multi robot motion planning and coordination. The current study proposes a hybrid framework for guidance and navigation of swarm of unmanned surface vehicles (USVs) by combining the key characteristics of formation control and cooperative motion planning. In this framework, two layers of offline planning and online planning are integrated and applied on a practical marine environment. In offline planning, an optimal path is generated from a constrained A* path planning approach, which is later smoothed using a spline. This optimal trajectory is fed as an input for the online planning where virtual target (VT) based multi-agent guidance framework is used to navigate the swarm of USVs. This VT approach combined with a potential theory based swarm aggregation technique provides a robust methodology of global and local collision avoidance based on known positions of the USVs. The combined approach is evaluated with the different number of USVs to understand the effectiveness of the approach from the perspective of practicality, safety and robustness.

Feasibility study of a constrained Dijkstra approach for optimal path planning of an unmanned surface vehicle in a dynamic maritime environment

Abstract: Optimal path planning is an important part of mission management hierarchy in a modern unmanned surface vehicle (USV) guidance, navigation and control frame work. USVs operate in a complex dynamic marine environment comprising of moving obstacles and sea surface currents. These characterising variables of configuration space change spatially as well as temporally. The current work investigates a well-known search technique, the Dijkstra algorithm, to resolve the problem of motion planning for a USV moving in a maritime environment. The current study extends the implementation of Dijkstra algorithm in a space cluttered with static and moving obstacles. In addition, downstream and upstream effects of sea surface currents of different intensities on optimal path planning are studied. The performance is verified in simulations with total path length and elapsed computational time considered as parameters to determine the effectiveness of the adopted approach. The results showed that the approach is effective for global path planning of USVs.

Towards use of Dijkstra Algorithm for Optimal Navigation of an Unmanned Surface Vehicle in a Real-Time Marine Environment with results from Artificial Potential Field

Abstract: The growing need of ocean surveying and exploration for scientific and industrial application has led to the requirement of routing strategies for ocean vehicles which are optimal in nature. Most of the op‐timal path planning for marine vehicles had been conducted offline in a self‐made environment. This paper takes into account a practical marine environment, i.e. Portsmouth Harbour, for finding an optimal path in terms of computational time between source and end points on a real time map for an USV. The current study makes use of a grid map generated from original and uses a Dijkstra algorithm to find the shortest path for a single USV. In order to benchmark the study, a path planning study using a well‐known local path planning method artificial path planning (APF) has been conducted in a real time marine environment and effectiveness is measured in terms of path length and computational time. http://www.transnav.eu the International Journal on Marine Navigation and Safety of Sea Transportation Volume 12

Guidance And Control Of Ocean Vehicles

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Optimal AUV pathplanning forextended missions incomplex, fast-flowing estuarine environments.

Abstract: This paper addressesthe problemsof automatically planning AutonomousUnderwater Vehicle (AUV)pathswhichbestexploit complex current data, from computational estuarine modelforecasts, whilealsoavoiding obstacles. Inparticular weexamine thepossibilities foranovel typeofAUV mission deployment infastflowing tidal river regions whichexperience bi-directional current flow. These environments are interesting in that,by choosing an appropriate pathinspaceandtime, anAUV maybothbypass adverse currents whicharetoofasttobeovercome bythe vehicle's motorsandalsoexploit favorable currents toachieve fargreater speeds thanthemotorscouldotherwise provide, while substantially saving energy. TheAUV can"ride" currents bothupanddowntheriver, enabling extended monitoring of otherwise energy-exhausting, fastflowenvironments. The paperdiscusses suitable pathparameterizations, costfunctions andoptimization techniques whichenable optimal AUV paths to be efficiently generated. Thesepathstakemaximum advantage oftheriver currents inordertominimize energy expenditure, journey timeandothercostparameters. The resulting pathplannercan automatically suggest useful alternative mission start andendtimes andlocations tothose specified bytheuser. Examples arepresented fornavigation in a simple simulation ofthefastflowing HudsonRiverwaters around Manhattan.

A survey of formation control and motion planning of multiple unmanned vehicles

Abstract: The increasing deployment of multiple unmanned vehicles systems has generated large research interest in recent decades. This paper therefore provides a detailed survey to review a range of techniques related to the operation of multi-vehicle systems in different environmental domains, including land based, aerospace and marine with the specific focuses placed on formation control and cooperative motion planning. Differing from other related papers, this paper pays a special attention to the collision avoidance problem and specifically discusses and reviews those methods that adopt flexible formation shape to achieve collision avoidance for multi-vehicle systems. In the conclusions, some open research areas with suggested technologies have been proposed to facilitate the future research development.

Path planning and collision avoidance for autonomous surface vehicles I: a review

Abstract: Autonomous surface vehicles are gaining increasing attention worldwide due to the potential benefits of improving safety and efficiency. This has raised the interest in developing methods for path planning that can reduce the risk of collisions, groundings, and stranding accidents at sea, as well as costs and time expenditure. In this paper, we review guidance, and more specifically, path planning algorithms of autonomous surface vehicles and their classification. In particular, we highlight vessel autonomy, regulatory framework, guidance, navigation and control components, advances in the industry, and previous reviews in the field. In addition, we analyse the terminology used in the literature and attempt to clarify ambiguities in commonly used terms related to path planning. Finally, we summarise and discuss our findings and highlight the potential need for new regulations for autonomous surface vehicles.