![challenge of the gobot challenge of the gobot](https://artworks.thetvdb.com/banners/graphical/76420-g2.jpg)
According to Research and Markets, the global autonomous mobile robot market accounted for $4.98 million in 2017 and is expected to reach $14.79 million by 2026, at a compound annual growth rate of 12.9%.
![challenge of the gobot challenge of the gobot](https://marcalliedotcom.files.wordpress.com/2021/01/gobots15.png)
Here Jonathan Wilkins, director at automation equipment supplier EU Automation, discusses the rise of mobile robots and what challenges need to be faced for their widespread uptake.ĪGVs were the original mobile robot technology but advances in both machine vision and navigation mean that more and more businesses are instead turning to autonomous mobile robots (AMRs). However, their reliance on environmental markers and the fact they follow a pre-determined route, means AGVs are best suited to working in structured environments in the absence of humans. Meaning if we have a Wall or Similar Stone within 3 Territories in any direction of our stone then we loosely own the area in between them.Automated guided vehicles (AGVs) have been an industry staple since 1953.We say we loosely own a territory if we have another stone within 3territories from us that can possible be used to surround.Loosely Owned Territory How we calculate: Loosely Owned Territory We can assume that we loosely own territory because it is only a few steps away from being captured Territory. Loosely Owned Territory No one has Any Territory and No Immediate danger of being captured. Not all moves gain Territory How do we consider the benefits of such moves?.H(move) = stones captured + white’s actual territory owned +(0.25) white’s loosely owned territory – black’s actual territory owned – (0.25) black’s loosely owned territory – stones lost Problem.Loosely Owned Territory Loosely owned Territory The actual territory is the number of intersections surrounded by a players stones on the board.To capture a stone (or stones) surround their immediate sides with.H(move) = stones captured + white’s actual territory owned + (0.25) white’s loosely owned territory – black’s actual territory owned – (0.25) black’s loosely owned territory – stones lost.MAXIMIN Tree The strongest new board will be chosen Strength = 2 Strength = 4 Strength = 1 MAXIMIN Tree Each one of the new boards will be evaluated according to its strength Strength = 4 Strength = 2 Strength = 1 MAXIMIN Tree Each new board will generate a tree of new boards Decides which stone placement will give the best possible outcome for the GoBot on the current board.The agent will use a MAXIMIN tree evaluation algorithm along with alpha-beta pruning to create possible actions.Key Algorithms We will use a simple heuristic to evaluate the “strength” of a board H(move) = stones captured + white’s actual territory owned + (0.25) white’s loosely owned territory – black’s actual territory owned – (0.25) black’s loosely owned territory – stones lost The decision making process of the agent will involve using a MAXIMIN tree to evaluate the strengths of each possible move. Summary Our project is to create an agent that will be able to play the game of Go on a competitive level against the members in our group. CHALLENGE OF THE GOBOTS Spring 2009 Midterm Mike Tran Chris Cuneo Arturo Salazar Allen Dunlea