PEAR: Geolocational AR Game

Key Methods
Game Design, Rapid Prototyping,
Software Architecture, UI Implementation

My Role
Leap Game Developer, Project Manager

Team
1 Lead Game Designer, 2 Game Developers,
2 3D Artists, 1 2D Artist, 2 Research Scientists,
1 Game Producer (who left mid-way)

Tools
Unity, C#, Photoshop, Figma, 3ds Max,
Jira, Confluence, Perforce

Duration
1 year, 2018-2019

Client
Project Oasis, SUTD-MIT International Design Center

Overview

The Scope
As part of Project Oasis, a larger research on environmental awareness by the SUTD-MIT International Design Center, they partnered with SUTD Game Lab to explore the potential of AR like Pokemon GO in inculcating positive environmental behaviours through physical interaction.

Plan

Early Concept & Rapid Prototyping

In this early concept phase, concepts were designed and rapid prototyped through paper demoes, UI mockups and interactive Unity prototypes.

Competitor Analysis
The game loops of educational games on environmental awareness and different types of AR games were studied. These helped inform our early concepts.

Early concepts & prototypes explored

• Grid-based GPS map city building mechanic

• Radius-based GPS map city building mechanic

• Environmental problems GPS map mechanic

• AR & geo-map split screen mechanic

• AR item scavenging mechanic

• AR pet mechanic

Agile Sprint Management

Game Development was split into a few core sprints, particularly narrative design, and the geolocation, AR Pet, AR Minigames, and Quest mechanics.

Project Development
Initially led by the game producer and afterwards me, using Jira and Confluence, Epics were broken down into sprint-based features across research, design, and development.
Led by me, 2D and 3D asset workflows were designed and taught to the artists to bridge assets from Photoshop and 3ds Max to Perforce and into Unity directly.

Core Game Loop
Led by the game designer, the core game loop is designed around 3 main game modes, Geolocation Map, AR Pet, and AR Minigames, with progress driven by quest system.
User’s pet scans for environmental minigames to tackle on the map, which requires energy to play. Energy tokens are collected from debris and rest stops on the map. Scan radius and item collection rates can be increased by interacting with the pet. Solving minigames and collecting quest items help complete quests, and progresses the storyline.

Software Architecture
Led by me, a main scene sits in the background, handling switching between the 3 core game modes, event management, and save/load of in-game data. This enables each game mode to be developed concurrently and modularly.

AR Pet

To build emotional attachment & play
As the Pear robot is the main AR companion, we wanted to create an AR pet mode where users can interact with it physically and nurture an emotional attachment.

Game Design
To encourage play, interactions are designed to influence Pear’s scan radius on the map. The higher Pear’s mood from play, the larger the scan radius.

Game Development
The AR Pet behaviour is designed with a state machine, with each interaction switching the state of the pet behaviour & triggering the intended animations.

Pet interactions

• PEAR’s expression & animation changes to his mood level

• Different idle animations are triggered when PEAR is left alone

• PEAR will chase after the user to stay within his camera view

• Rubbing PEAR trigger a set of ‘purr’ responses

• Poking PEAR will tickle it, and cause it to retreat into its shell

• Dragging PEAR around will cause it to wiggle out of your hold

Early designs of AR toys and interactions were also explored for future expansions.

AR Minigames

The Goal: Inculcate Positive Environmental Behaviours
Educating users on environmental awareness and positive actions is a core goal of the project. Each minigame is designed around educating and engaging users with a particular environmental problem, through physical engagement using AR or VR.

Game Design for Replayability
As assessed and tested, the ideal duration for each minigame is around 60 seconds. As the game progressed, minigames will vary in difficulty, with dynamically generated level layouts and difficulty scaled elements to ensure replayability.

Game Development for for Scale
Each minigame is designed to be modular and independent, with a minigame API developed to allow additional minigames to be proposed and designed by external partners.

Minigames developed

• Water Pollution
  In an underwater environment, user moves their phone around in AR to vacuum and collect litter, while avoiding the sea creatures.
  Litter placements, drifts and marine creatures are adjusted as difficulty increases in late game.
  At the end, users are informed of their efforts in comparison to the amount of pollution in the sea.

• Electricity Conservation
  In an indoor environment, user moves their phone around in AR to locate appliances that are switched on and tap to turn them off.
  Different indoor environment locations, appliance types and arrangements are randomised for replayability.
  At the end, users are informed of the electricity they potentially saved, scaled up to a year across a city.

• Recycling
  Users recycle litter into different types of bins through AR paper toss, while remembering to clean contaminated litter before recycling.
  Litter types, bin types and placements are adjusted as difficulty increase in late game.
  Through playing, users will identify what litter can or cannot be recycled, and to clean contaminated litter before recycling.

• Afforestation
  Users scan the ground to uncover fertile soil suitable for planting seeds. However, the scan does not last and requires time to recharge.
  Grid layout and arrangements are randomised for replayability.
  At the end, users are informed of how many plants they potentially planted and their impact, scaled up to an hours time.

For more details on Pear, please reach me at mail@alanng.me