In the middle of 2016, me and my partner Torben decided to study a few business spaces. The criteria was to pick the idea we loved the most out of those where our competences and resources combined could result in a differentiated offering.
We both loved the potential to tackle the software stack fragmentation in the unmanned vehicles market. Unmanned vehicles in this context includes air, ground, surface and the underwater kind. We developed a strategic document with two main references for strategic positioning. I have included them here for your reference, click the links to download!
In the market segmentation analysis, we explored two axis. A vertical axis for activities, in terms of the type interaction with the environment required by the application. We started with Tinkering (none required), then Playing (in an environment), then Acquiring data (sensing the environment), then Surveillance (acting on repeatedly sensed data), then Transportation (of things in the environment) and finally Actuation (changing the environment). The other axis has the medium of operation, from Air (UAV), to Ground (UGV), to Surface (USV), to Underwater (UUV). It's also split, where we found appropriate, into Public (eg. streets or a lake) or Private (eg. your house or a warehouse). For each of the opportunities created in the intersection of axis we then added examples, and assessed the potential according to a number of criteria.
Software Stack analysis
We also produced a preliminary analysis of different sw stacks for operating unmanned vehicles. More important than the data, which is becoming rapidly stale, is the taxonomy. It starts with 3 top-level pieces of the stack. The first is an Onboard Command & Control software, which the sw that is inside each drone or each vehicle. The second is Communication, which includes all about the protocol and application-level command support of the stack. The last one is the Remote Command & Control, usually known as the Ground station. It's the tool a human or a team use to issue missions, plans, actions to the vehicles, to observe the behaviour of the vehicles, and to handle payload.
FYI, we ended up pursuing something else. But this space is truly great. I have to thank the lab LSTS all the inspiration and support they gave me in this data compilation and analysis. Ping me for any question you may have!