Persistent AUV Operations Using a Robust Reactive Mission and Path Planning (RRMPP) Architecture (original) (raw)
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ArXiv, 2016
Providing a higher level of decision autonomy is a true challenge in development of today AUVs and promotes a single vehicle to accomplish multiple tasks in a single mission as well as accompanying prompt changes of a turbulent and highly uncertain environment, which has not been completely attained yet. The proceeding approach builds on recent researches toward constructing a comprehensive structure for AUV mission planning, routing, task-time managing and synchronic online motion planning adaptive to sudden changes of the time variant environment. Respectively, an "Autonomous Reactive Mission Scheduling and Path Planning" (ARMSP) architecture is constructed in this paper and a bunch of evolutionary algorithms are employed by different layers of the proposed control architecture to investigate the efficiency of the structure toward handling addressed objectives and prove stability of its performance in real-time mission task-time-threat management regardless of the applie...
ArXiv, 2016
Today AUVs operation still remains restricted to very particular tasks with low real autonomy due to battery restrictions. Efficient motion planning and mission scheduling are principle requirement toward advance autonomy and facilitate the vehicle to handle long-range operations. A single vehicle cannot carry out all tasks in a large scale terrain; hence, it needs a certain degree of autonomy in performing robust decision making and awareness of the mission/environment to trade-off between tasks to be completed, managing the available time, and ensuring safe deployment at all stages of the mission. In this respect, this research introduces a modular control architecture including higher/lower level planners, in which the higher level module is responsible for increasing mission productivity by assigning prioritized tasks while guiding the vehicle toward its final destination in a terrain covered by several waypoints; and the lower level is responsible for vehicle's safe deploym...
2016
Today AUVs operation still remains restricted to very particular tasks with low real autonomy due to battery restrictions. Efficient motion planning and mission scheduling are principle requirement toward advance autonomy and facilitate the vehicle to handle long-range operations. A single vehicle cannot carry out all tasks in a large scale terrain; hence, it needs a certain degree of autonomy in performing robust decision making and awareness of the mission/environment to trade-off between tasks to be completed, managing the available time, and ensuring safe deployment at all stages of the mission. In this respect, this research introduces a modular control architecture including higher/lower level planners, in which the higher level module is responsible for increasing mission productivity by assigning prioritized tasks while guiding the vehicle toward its final destination in a terrain covered by several waypoints; and the lower level is responsible for vehicle's safe deploym...
Adaptive AUV mission management in under-informed situations
OCEANS 2010 MTS/IEEE SEATTLE, 2010
Autonomous Underwater Vehicles (AUVs) are in high demand within the offshore industry and maritime research, mainly used for bathymetry and data acquisition. The control architectures of these AUVs mimic this primary function by focusing on strict mission plans as these kind of application require, thus reducing the need for direct sensor reaction to emergency situations. The emerging needs for more complex underwater application like the inspection of structures, search missions or taking samples from the floor or in the water column with respect to certain environmental conditions demand more adaptive, currently not existing, control architectures. The main problem hereby is that, opposed to non-underwater application scenarios for autonomous systems, the lack of a stable communication channel to the vehicle demands complete autonomy. The architecture proposed in this paper aims at tackling the issue of unpredictability. The main issue, especially in exploration or inspection missions, is that little is known at the beginning of the mission. This lack of information makes planning meaningless, as the planner has no idea whatsoever as to what should be done while on site. Our proposed architecture offers to replace, in these under-informed situations, planning-based approaches by a plan management approach. This approach is able to use both predictive (planning) approaches and behaviours (reactive) approaches to control the system, which is then used to execute and control execution of functional components. The mixing of these decision-making schemes being done based on the information available to the system. This paper presents the general idea of our architecture as well as the implementation and a validation experiment with the AUV AVALON.
AUTONOMOUS AUV MISSION PLANNING AND REPLANNING - TOWARDS TRUE AUTONOMY
This paper discusses concepts developed under the SEA led UK MoD Battlespace Access Unmanned Underwater Vehicle (BAUUV) programme to provide higher levels of military AUV autonomy. BAUUV aims to identify and assess the technology readiness relating to a range of future (2010-2015) UK military missions and to perform focussed technology development activities to address key technology gaps. One key gap relates to provision of suitable levels of autonomy to allow a UUV to perform long duration military missions. Contemporary autonomous underwater vehicles generally execute a prescripted mission plan with simple branching. However, future military missions will require higher levels of autonomy such that the vehicle can operate with a minimum of supervision and adapt to changing military goals, onboard health and situational awareness. In order to reduce onerous and often impracticable human supervision and communications requirements, future military vehicles will need to perform some level of autonomous mission replanning and decision making in order to adapt to changes in AUV situational awareness, changes in knowledge of vehicle status and energy availability and changes in military goals. Autonomous mission replannning algorithms that aim to provide this functionality have been developed and evaluated. The resulting mission replanning software utilises a hierarchical iterative approach with initial rough planning based on goal selection and sequencing activities being followed by detailed task planning and plan tuning. Replans can be instigated by user defined changes in goal characteristics or priorities or by internal triggers such as an unexpected change in energy usage or task progress. In addition to core mission replanning algorithms, software relating to specific task planning/replanning modules is being considered. For example, an autonomous transit task planner has been developed. This is capable of autonomously defining and costing a transit based on encyclopaedic knowledge of subsurface currents, detection and physical risks. The AUV “personality” is defined by the relative vehicle energy, risk and time priorities which drive the selection of a particular transit plan. Other task planners being considered include those relating to communications, survey, reconnaissance, REA and logistics goals. Within a typical three-layer UUV hierarchical control architecture, the onboard mission and task replanning elements would form part of the top level deliberative elements and would typically interface to a sequencing layer via an updatable mission script. The sequencing layer would interface to task achieving behaviours and low level autopilot modes, potentially via a collision and obstacle avoidance module. In addition to onboard elements, this paper discusses associated concepts relating to intuitive user interfaces and planning aids. Goal based planning/replanning technology enables the user to specify a mission based on a series of military goals, constraints and priorities rather than having to define a detailed mission script. This should increase the speed for the definition, validation and modification of future missions and reduce the skill requirement for a future military UUV user. An example goal based user interface prototype is presented. Finally, after describing current study results and status, the paper will touch upon ongoing trial activities to advance the technology from TRL 4/5 to TRL 6.
Autonomous Planning and Mission Management for Future Military AUVs
Contemporary Autonomous Underwater Vehicles generally execute a prescripted mission plan with simple branching. However, future long duration military missions will require higher levels of autonomy such that the vehicle can operate with a minimum of supervision and adapt to changing military goals, onboard health and situational awareness. This paper discusses concepts developed under the SEA led UK MoD BAUUV programme to provide higher levels of military AUV autonomy. These include Intuitive User Interfaces that assist the user in specifying missions in terms of military goals rather than detailed scripts, Autonomous Onboard Mission Planning/Replanning software that enables the vehicle to autonomously adjust to changes in goals or status, Transit Planning Software that autonomously plans routes based on subsurface currents, risks and "personality" weightings and dedicated autonomous task planning modules. These concepts have been evaluated in simulation and will be implemented within water-based trials.
Onboard adaptive control of AUVs using automated planning and execution
2009
In this paper we describe an integrated goal-oriented control architecture for onboard decision-making for AUVs. Onboard planning and execution is augmented by state estimation of perceived features of interest in the coastal ocean, to drive platform adaptation. The partitioned architecture is a collection of coordinated control loops, with a recurring sense, plan, act cycle and which allows for plan failures to be localized within a control loop and ensures a divide-and-conquer approach to problem solving in dynamic environments.
An Online AUV Trajectory Re-planning Software Architecture Based on the MOOS
This paper discusses an open source navigation system architecture uniquely suited to use in autonomous underwater vehicles. It is based on the Mission Oriented Operating System developed by Newman (2006), Newman (2008). Some of its most pronounced advantages are an orientation towards providing a tool set for rapid prototyping of new control algorithms and support for development-stage software design in AUV systems. Its advantages are a direct result of the MOOS's completely modular nature, and the presented architecture has been built to preserve and, where possible, enhance this modularity. Using the MOOS design templates, control algorithms are encoded as applications "living" in separate processes of the operating system kernel. This methodology provides for a level of robustness instrumental in autonomous vehicle since failures and errors will cause only the individual modules that incur them to fail and corresponding processes to be "killed" by the operating system. Such critical occurrences will thereby be contained and their propagation halted from completely freezing even the low-level control loops and decision-making processes needed to successfully retrieve the malfunctioning AUV.
ArXiv, 2016
The AUV three-dimension path planning in complex turbulent underwater environment is investigated in this research, in which static current map data and uncertain static-moving time variant obstacles are taken into account. Robustness of AUVs path planning to this strong variability is known as a complex NP-hard problem and is considered a critical issue to ensure vehicles safe deployment. Efficient evolutionary techniques have substantial potential of handling NP hard complexity of path planning problem as more powerful and fast algorithms among other approaches for mentioned problem. For the purpose of this research Differential Evolution (DE) technique is conducted to solve the AUV path planning problem in a realistic underwater environment. The path planners designed in this paper are capable of extracting feasible areas of a real map to determine the allowed spaces for deployment, where coastal area, islands, static/dynamic obstacles and ocean current is taken into account and ...
2016
Promoting the levels of autonomy facilitates the vehicle in performing long-range operations with minimum supervision. The capability of Autonomous Underwater Vehicles (AUVs) to fulfill the mission objectives is directly influenced by route planning and task assignment system performance. This paper proposes an efficient task-assign route planning model in a semi-dynamic operation network, where the location of some waypoints are changed by time in a bounded area. Two popular meta-heuristic algorithms named biogeography-based optimization (BBO) and particle swarm optimization (PSO) are adopted to provide real-time optimal solutions for task sequence selection and mission time management. To examine the performance of the method in a context of mission productivity, mission time management and vehicle safety, a series of Monte Carlo simulation trials are undertaken. The results of simulations declare that the proposed method is reliable and robust particularly in dealing with uncertainties and changes of the operation network topology; as a result, it can significantly enhance the level of vehicle's autonomy by relying on its reactive nature and capability of providing fast feasible solutions.