Robotic colonies that can communicate with each other and interact with their ambient environments can be utilized for a wide range of research and industrial applications. However amongst the problems that these colonies face is that of the isolating objects within an environment. Robotic colonies that can isolate objects within the environment can not only map that environment in detail, but interact with that ambient space. Many object recognition techniques exist, however these are often complex and computationally expensive, leading to overly complex implementations. In this paper a simple model is proposed to isolate objects, these can then be recognize and tagged. The model will be using 2D and 3D perspectives of the perceptual data to produce a probability map of the outline of an object, therefore addressing the defects that exist with 2D and 3D image techniques. Some of the defects that will be addressed are; low level illumination and objects at similar depths. These issues may not be completely solved, however, the model provided will provide results confident enough for use in a robotic colony.

Robotic agents are now ubiquitous in both home and work environments; moreover, the degree of task complexity they can undertake is also increasing exponentially. Now that advanced robotic agents are commonplace, the question for utilisation becomes how to enable collaboration of these agents, and indeed, many have considered this over the last decade. If we can leverage the heterogeneous capabilities of multiple agents, not only can we achieve more complex tasks, but we can better position the agents in more chaotic environments and compensate for lacking systems in less sophisticated agents. Environments such as search and rescue, agriculture, autonomous vehicles, and robotic maintenance are just a few examples of complex domains that can leverage collaborative robotics. If the use of a robotic agent is fruitful, the question should be: How can we provide a world state and environment mapping, combined with a communication method, that will allow these robotic agents to freely communicate? Moreover, how can this be decentralised such that agents can be introduced to new and existing environments already understood by other agents? The key problem that is faced is the communication method; however, when looking deeper we also need to consider how the change of an environment is mapped while considering that there are multiple differing sensors. To this end, we present the voxel grid approach for use in a decentralised robotic colony. To validate this, results are presented to show how the single-agent and multiagent systems compare.