What began as a humble meeting of machine learning and artificial intelligence scientists in Germany in 1998, dubbed the "KI-98: Advances in Artificial Intelligence" outlined by Otthein Herzog and Andreas Gunter, would serve as a purveyor of truth for the coming future of courier services. Specifically, in the conference the machine named FAXBOT was the topic of ample scientific intrigue, as FAXBOT was touted as an autonomous robot office courier that applied communication actions necessary to carry out ambiguous commands and deal with situations that the robots of 1998 could not deal with at the time. For 1998, this was mere scientific fiction being hypothesized and thrown against the wall to see if anything would stick. The ensuing result was not only a hypothesized robot that stuck, but was only being discussed at the most nascent of stages.
The world of possibilities in delivery command far exceed whatever ambiguous command or unplanned language dialogue. It meant something requiring intuitive and thought-provoking intelligence was to be derived. And so it would. In 2013, a quantum leap in the application of applied intelligent systems was made thanks to the publication of Qian Hu, Andrew Lim, and Wenbin Zhu, titled "The Two-Dimensional Vector Packing Problem with Courier Cost Structure", where we see a more specialized application of intelligence being researched. Here, the two-dimensional vector packing problem with courier cost structure is a practical problem faced by many manufacturers that ship products using courier service. The manufacturer must ship a number of items using standard-sized cartons, where the cost of a carton quoted by the courier is determined by a piecewise linear function of its weight. The cost function is not necessarily convex or concave. The objective is to pack all items into cartons such that the total delivery cost is minimized while observing both the weight limit and volume capacity constraints.
Two key areas of the courier and delivery supply chain are currently being exploited by artificial intelligence platforms, and Senpex is positioning itself with several cornerstone software partnerships to develop alongside this disruption of the industry.
Logistics automation platform
Logistics automation platform manages requested deliveries automatically without the need of human involvement or supervision. The provided platform contains various applications for users and allows to automate every step of the delivery efficiently. An artificial intelligence module makes sure that they system can learn and perform better based on collected data.
Courier robots with the sensor-fusion platform
Courier robots can be requested by users on demand. Thanks to the sensor-fusion platform, courier robots can drive fully autonomously. The sensor-fusion platform collects the data from different sensors on the robot like GNSS receiver, Lidar, Camera, etc., and filters the data to verify the current position of the robot and to navigate the robot to the target. All the data is processed directly in the robot, allowing quick reaction of the robot in the case of unexpected obstacles.
In the future, Senpex foresees another area of groundbreaking innovation: quantum computing alongside machine learning; both working to further refine the back-end process of logistics to work in synchronization with the front-end. This will ensue rapidly, so much so, that it will see an inevitable state of deminishing marginal returns. Is it only when the industry has reached this state that we have entered so-called logistical utopia? Either way, Senpex stands ready for such a day to arrive.