Abstract: Distant semi-autonomous systems containing their own processors and are capable of thinking for themselves, and to some extent, controlling lower functions is provided herein. These semi-autonomous systems may be referred to as “nodes”. The network is not dependent on actual protocol or network topology. The brain, one or more central multiprocessors, is only tasked with issuing simpler, higher-level commands such as “faster” or “slower”, or “execute a grabbing motion”. These commands are then interpreted and executed by the nodes.

Abstract: A method for decision-making by an electronic system comprising a plurality of components is provided herein. The components of the system are given tunable voting authority v=[Vmin . . . Vmax], typically [?1 . . . 1]. A singleton officiating member manages the notification and voting process. A current representation of the entire system is stored in the model. The model is a state storage system that tracks the existence and condition of a group of tracked data items, called Entities. The model is managed by the singleton officiating member but may be queried by any component.

Abstract: A method for human-arbitrated conflict resolution within autonomous vehicle control system is provided herein. Autonomous operation and capabilities of an unmanned vehicle, such as an urban delivery vehicle, are improved by incorporating an onboard programmable decision unit that operates in an essentially autonomous fashion under normal operating conditions. When dynamic, changing, or unexpected conditions are encountered within the vehicle's environment, an on-board decision making unit decides how to best overcome any problems should they arise. A human operator may interact with the vehicle to resolve a conflict if an intervention delta is exceeded.

Abstract: A method for manually or semi-manually mapping an urban environment to locate a safe, traversable path within the environment is provided herein. An area is mapped by an entity that traverses sidewalks, ramps, driveways, crosswalks, and other terrain in the area to create a memory of usable paths to reach addressed destinations. A human operator, possibly assisted by a computer-executed mathematical algorithm, approves routes that are considered safe. When a route is approved, it enters the memory as a safe, traversable route. If a route is not approved, it is marked as unsafe and the entity finds an alternate route to get to the same location such as by going around the block or in another direction.

Abstract: A method for manually or semi-manually re-mapping an urban environment during delivery operations by an autonomous vehicle is provided herein. In an embodiment of the invention, an autonomous delivery vehicle performs delivery operations within an urban environment. The urban environment can comprise a city or a portion of a city such as a neighborhood. The autonomous vehicle traverses along a previously mapped and scanned route that has been determined to be safe and traversable for the delivery vehicle. As it traverses the route, the delivery vehicle scans the route again using the same sensors that were used to scan the route initially. If a sensor delta is exceeded, the vehicle may execute any one or combination of notifying an operator, deciding, choosing a different route, continuing, or executing a contingency plan.