An Autonomous Reactive Architecture for Efficient AUV Mission Time Management in Realistic Severe Ocean Environment (original) (raw)
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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...
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.
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...
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.
2016
Expansion of today's underwater scenarios and missions necessitates the requestion for robust decision making of the Autonomous Underwater Vehicle (AUV); hence, design an efficient decision making framework is essential for maximizing the mission productivity in a restricted time. This paper focuses on developing a deliberative conflict-free-task assignment architecture encompassing a Global Route Planner (GRP) and a Local Path Planner (LPP) to provide consistent motion planning encountering both environmental dynamic changes and a priori knowledge of the terrain, so that the AUV is reactively guided to the target of interest in the context of an unknown underwater environment. The architecture involves three main modules: The GRP module at the top level deals with the task priority assignment, mission time management, and determination of a feasible route between start and destination point in a large scale environment. The LPP module at the lower level deals with safety consid...
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.
Persistent AUV Operations Using a Robust Reactive Mission and Path Planning (RRMPP) Architecture
arXiv: Robotics, 2016
Providing a higher level of decision autonomy and accompanying prompt changes of an uncertain environment is a true challenge of AUVs autonomous operations. The proceeding approach introduces a robust reactive structure that accommodates an AUV's mission planning, task-time management in a top level and incorporates environmental changes by a synchronic motion planning in a lower level. The proposed architecture is developed in a hierarchal modular format and a bunch of evolutionary algorithms are employed by each module to investigate the efficiency and robustness of the structure in different mission scenarios while water current data, uncertain static-mobile/motile obstacles, and vehicles Kino-dynamic constraints are taken into account. The motion planner is facilitated with online re-planning capability to refine the vehicle's trajectory based on local variations of the environment. A small computational load is devoted for re-planning procedure since the upper layer mis...
Journal of Intelligent & Robotic Systems, 2018
This paper presents a hybrid route-path planning model for an Autonomous Underwater Vehicle's task assignment and management while the AUV is operating through the variable littoral waters. Several prioritized tasks distributed in a large scale terrain is defined first; then, considering the limitations over the mission time, vehicle's battery, uncertainty and variability of the underlying operating field, appropriate mission timing and energy management is undertaken. The proposed objective is fulfilled by incorporating a route-planner that is in charge of prioritizing the list of available tasks according to available battery and a pathplaner that acts in a smaller scale to provide vehicle's safe deployment against environmental sudden changes. The synchronous process of the task assign-route and path planning is simulated using a specific composition of Differential Evolution and Firefly Optimization (DEFO) Algorithms. The simulation results indicate that the proposed hybrid model offers efficient performance in terms of completion of maximum number of assigned tasks while perfectly expending the minimum energy, provided by using the favorable current flow, and controlling the associated mission time. The Monte-Carlo test is also performed for further analysis. The corresponding results show the significant robustness of the model against uncertainties of the operating field and variations of mission conditions.
Mission Control of the MARIUS AUV: System Design, Implementation, and Sea Trials
International Journal of Systems Science - IJSySc
This paper describes the design and implementation of a Mission Control System for the MARIUS Autonomous Underwater Vehicle (AUV). The framework adopted for system design builds on the key concept of Vehicle Primitive, which is a parameterized specification of an elementary operation performed by the vehicle. Vehicle Primitives are obtained by coordinating the execution of a number of concurrent System Tasks, which are parameterized specifications of classes of algorithms or procedures that implement basic functionalities in an underwater robotic system. Vehicle Primitives are in turn logically and temporally chained to form more abstract Mission Procedures, which are executed as determined by Mission Programs, in reaction to external events. System Task design is carried out using well established tools from continuous/discrete- time dynamic system theory, and finite state automata to describe their logical (event-based) interaction with Vehicle Primitives. The design and analysis ...