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  | text = (3.0 Page Maximum) – Describe the technical approach that your team will use to achieve the degree of autonomy necessary to accomplish each of the tasks in the competition as described on the RobotX 2022 competition page. The technical rationale and approach must identify the RobotX tasks that will be attempted, strategies to complete the tasks, and proposed approach to address any technical issues encountered. The Applicant’s capacities must be discussed as they relate to achieving success in the project. A timeline for system development and testing should be included.

  | text = (3.0 Page Maximum) – Describe the technical approach that your team will use to achieve the degree of autonomy necessary to accomplish each of the tasks in the competition as described on the RobotX 2022 competition page. The technical rationale and approach must identify the RobotX tasks that will be attempted, strategies to complete the tasks, and proposed approach to address any technical issues encountered. The Applicant’s capacities must be discussed as they relate to achieving success in the project. A timeline for system development and testing should be included.

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The competition focuses on autonomy and its execution in an integrated system-of�systems, built around the WAM-V platform. This will require an understanding of systems

engineering, including sensor fusion, autonomy development and integration, and testing across a range of environmental conditions. Describe the technical approach that your team will use to achieve the degree of autonomy necessary to accomplish each of the tasks in the competition as described on the RobotX 2022 competition page.  

2022 will be the first OCRobotX Team event, and will present significant challenges. Primarily, raising the money to purchase the material items required, and travel costs associated with the competition in Australia. Moreover, the basic task of putting together a complete engineering group, and designing from startup the primary WAM-V Subsystems, coupled with the AI development, will likely force the team to confine itself to the Maritime Platform only and forego the UAV component of the competition.  The WAM-V focus only, should not be considered an under-achievement by any means, considering the short ramp-up.

Key areas of consideration include the following:

#Summary of hardware and software approaches to accomplishing all tasks. This should include the types of sensors required to collect data in-situ, computational infrastructure to process and integrate multiple types of data and make decisions based on situational knowledge.  

There are four major essential areas that must be designed, integrated, and proven, prior to any major sensor package development. Namely, the Ground Control Station (GCS), Onboard Mission Manager (MM), and the radio inter-connectivity frameworks—long range WIFI—the GCS and MM require the greatest amount of planning, design and testing.  This design and testing should include forward thinking analysis of sensor capability and expansion.  Secondarily, propulsion, power distribution and power management systems have almost equal importance to the overall success of the project mission rounding out the four areas.  The goal is to develop a robust operating system design, scalable to handle the addition of sensors such as LIDAR, SONAR, RADAR, GPS/IMU, HD Vision and perception, as well as environmental weather, set and drift indicators/detectors, and propulsion control and feedback. The lack of rock-solid navigation, and positional uncertainty problems have plagued many of the RobotX competitors in the past.  While the EE/CS team focuses on the computing infrastructure being constructed and tested. The ME teams will focus on the propulsion design and testing with two major goals: designing the propulsion control system to function under direct remote control—essential for initial deployment and placement of the platform—and secondly, semi-autonomous control via the GCS and MM, using waypoint concepts integrated with GPS and platform drift.  Every attempt will be made to prove algorithm by algorithm performance, first with simulation, then a technique called ‘hardware-in-the-loop’. Hardware-in-the-loop consists on systematically replacing simulated sections, piece by piece, with real hardware proving the stimulus processing is reliable. Designing the MM this way allows for Sim-to-Hardware swap if a Subsystem fails and trouble-shooting in the field needs to take place.  This technique also allows a complete system and pseudo-mission rehearsal prior to each in-water event.

#Plan for testing the approaches described (laboratory, field experiments, simulation, etc.).  

#Strategies to overcome a failure of any component or system critical to accomplishing the tasks (system redundancy, multiple sensor inputs, etc.).

Several of the RobotX team members in late 2019, designed and constructed a CrawlerBot (see http://ocrobotx.org/mediawiki/index.php/Holonomic_Robotic_Platform#Project_Purpose) using holonomic drive techniques in anticipation of using that experiential knowledge as an approach vector to design a more complex WAM-V propulsion system. It is apparent to the experienced team members that a combination of straightforward linear propulsion systems that can be mechanically articulated into a holonomic drive system presents the best of both options: speed when needed, and fine-grained maneuverability required to complete complex navigation maneuvers.

#Strategies for understanding behavior of autonomous system (situational awareness).

Power management presents a large opportunity for design consideration with respect to the computing network and infrastructure for sensor data processing, and AI backbone.  Raspberry PI 4 computing has proven itself to be a very capable processing platform, hosting Python, MATLAB APIs, and other AI plugins.  Distributed computing of multiple PIs can provide cluster computing performance, at literally a fraction of the super-computer cost, and using a miniscule amount of the power consumption. Linux, ROS, Python, and MATLAB are the primary software staples of the processing infrastructure required to complete the project, as well as embedded microcontroller devices similar to Arduinos.

===Technical Approach and Justification here===

 

====Integrated Team Development (a.k.a. Divide an Conquer Approach)====

  Three primary sensor inputs, as well as advanced processing must be achieved to meet minimum competition status, namely:  LIDAR, Vision and perception, and GPS/IMU. The EE/CS teams will divide the tasks among smaller working groups with articulated development and test events, as well as key subsystem integration milestones.  LIDAR processing, vision mapping and AI perception, as well as occupancy grid development becomes critical as the project timeline progresses, since all of the competition tasks rely on mapping the field and interacting appropriately with the objects located in the range.  The team has allocated funds to construct training aids to be deployed along with the WAM-V test phases, providing a competition range facsimile for training. 

====Four part Harmony====

Secondary sensor development involves depth sounding/echo sounding sensors for bottom contour mapping which facilitates ground collision avoidance. Finally, SONAR ping detection, discrimination, ranging, and localization is also required to negotiate several of the competition challenges.

The primary design of unmanned systems consist of four major areas on concentration:

The ME teams’ secondary task is to develop the projectile launcher required for the ‘Dock and Deliver Challenge’.  The in-water testing phase will primarily occur after the Vision-Perception algorithms and hardware have been range tested.

#Command and Control (C&C: the semi-autonomous and autonomous control systems)

#Sensor Package (environmental inputs to the C&C in 3D space)

All design, development and test phases will be documented scrupulously as part of the team academic rigor.  The OCRobotX team will employ the concept of ‘The Digital Ecosystem’. The digital ecosystem (DE) goes hand-in-hand with the concept of Subsystem Integration plan.  All team members will be trained to understand the significance of digital artifacts and how these products support the project.

Digital artifacts are defined as: project specifications, technical drawings, design documents, interface management documents, analytical results, bills of material (BOM), work breakdown structures (WBS), machining instructions, test procedures and test results and lastly schedules to include development, design, building, test, and integration. The project leadership is responsible for communicating the requirements as well as the appropriate artifacts and their purpose. The primary importance of digital artifacts becomes apparent during system integration, and producing the engineering paper required for the RobotX presentation. One critical function the DE fills, is to produce Objective Quality Evidence (OQE) to relevant stake holders, proving the engineering team has reached specific milestones in the development project, e,g. satisfying a progress audit by ONR, or WSU and OC staff.  Since all of the DE is considered non-proprietary by RoboNation Standards, the OCRobotX team has opted to make all of the DE available at any time to the public via the OCRobotX Wiki located at: http://ocrobotx.org/mediawiki/index.php/Main_Page. The OC engineering club has most of the minutes published online since the first club meeting where the decision was made to participate in the competition (see http://ocrobotx.org/mediawiki/index.php/OC_Engineering_Club org).

#The Energy Systems (ES:Power and Power control systems).

===AI Focus===

Design efficiency in learning heuristics will leverage work by previous team publications.  The team will work to design an AI that is capable of determining the efficacy of its own decision making, i.e., the probability of mission success. This feedback can help the designers shape the machine and deep learning algorithms to maximize mission performance. One particular example would be an AI that monitors the power system to determine if the platform has the energy required to complete a range of tasks.

===Time line Projection===

The master timeline for fundraising and development will take all of the time between the summer of 2021 through to November of 2022. A detailed Work Breakdown Schedule is embedded as two Gantt charts weekly and monthly.  It is expected that momentum for the project will grow past the twenty students listed if ONR awards the platform to the OC-WSU Team.

==<big>'''Team Qualifications'''</big>==

==<big>'''Team Qualifications'''</big>==