Drone-based mud softening treatment device
A mud treatment system that can be used during emergencies is disclosed. The system includes an autonomous vehicle carrying a mud treatment device. In response to information about a mud-related disaster at a specific location, the system will instruct the vehicle to travel to the location, enter a building, and dispense one or more applications of mud softener in the interior space of the building. The vehicle can navigate from room to room and determine whether moisture content levels are below a specified threshold. In response, the vehicle can direct its mud or dirt softening efforts to these specific zones.
1 . A method of providing mud treatment services at a target location, the method comprising:
obtaining, at a first time and via a first sensor of a first autonomous vehicle navigating inside of a first building at the target location, first sensor data about a first portion of a first room in the first building;
detecting, via an onboard computing system for the first autonomous vehicle and based on the first sensor data, a first mudflow in the first portion;
determining, at an onboard computing system for the first autonomous vehicle and based on the first sensor data, that a first moisture content level for the first mudflow is less than a first threshold level; and
causing, via the onboard computing system and at a second time, a mud softener device installed on the first autonomous vehicle to dispense a first application of softener onto the first mudflow.
2 . The method of claim 1 , wherein the first mudflow has a first volume at the first time and a greater, second volume at the second time.
3 . The method of claim 1 , further comprising:
obtaining, via the first sensor, second sensor data about a second portion of the first room;
detecting, via the onboard computing system for the first autonomous vehicle and based on the second sensor data, a second mudflow in the second portion;
determining, at an onboard computing system for the first autonomous vehicle and based on the second sensor data, that a second moisture content level for the second mudflow is greater than the first threshold level; and
causing, via the onboard computing system, the first autonomous vehicle to navigate away from the second portion.
4 . The method of claim 1 , further comprising:
obtaining, via the first sensor, second sensor data about a second portion of the first room;
detecting, via the onboard computing system for the first autonomous vehicle and based on the second sensor data, a second mudflow in the second portion;
determining, at an onboard computing system for the first autonomous vehicle and based on the second sensor data, that a second moisture content level for the second mudflow is less than the first threshold level; and
causing, via the onboard computing system, the first autonomous vehicle to navigate toward the second portion.
5 . The method of claim 4 , wherein the hole is a tunnel extending from a first side of the wall to a second side of the wall, and the method further comprises causing, via the onboard computing system, the mud treatment device to dispense, through the tunnel, a second application of mud softener into a space that is adjacent to the second side of the wall.
6 . The method of claim 1 , further comprising:
transmitting, prior to the first time, a first signal identifying the target location from a remote computing system for a mud treatment service to the first autonomous vehicle, the first autonomous vehicle being stationed in a drone repository; and
causing, via the onboard computing system and in response to the first signal, the first autonomous vehicle to execute a path from the drone repository to the target location.
7 . The method of claim 6 , further comprising:
determining, via the onboard computing system, that an assessment of the first building has been completed;
causing, via the onboard computing system, the first autonomous vehicle to execute a return path from the target location to the drone repository;
transmitting, after the first autonomous vehicle executes the return path, a second signal identifying the target location from the remote computing system for a mud removal service and navigation guidance to the first portion to a second autonomous vehicle, the second autonomous vehicle being stationed in the drone repository;
causing, in response to the second signal, the second autonomous vehicle to execute a path from the drone repository to the first portion at the target location; and
causing a vacuum device for the second autonomous vehicle to remove the first mudflow.
8 . The method of claim 1 , further comprising:
determining a level of softener stored in a tank of the mud treatment device has fallen below a minimum level;
causing, via the onboard computing system, the first autonomous vehicle to execute a path from inside the first building to an exterior environment near the first building where a pool of water is present; and
refilling the tank with water available in the pool of water.
9 . A drone-based mud treatment system, comprising:
an unmanned autonomous vehicle;
a mud treatment device installed on the autonomous vehicle including a container for storage of a mud softening agent;
a plurality of mud detection sensors; and
an onboard computing system.
10 . The system of claim 9 , further comprising a remote server configured to transmit a signal to the autonomous vehicle indicating a target destination to which it should travel.
11 . The system of claim 9 , further comprising a robot arm with an end effector extending from a housing of the autonomous vehicle, the end effector comprising a spindle configured to tap and drill holes in walls.
12 . The system of claim 9 , further comprising a robot arm with an end effector extending from a housing of the autonomous vehicle, the end effector comprising an opening for dispensing of the mud softening agent.
13 . The system of claim 12 , wherein the robot arm includes a channel extending from a first end to the opening in the end effector, the first end being in fluid communication with the contents of the container.
14 . A system for providing mud treatment services at a target location, the system comprising one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to:
obtain, at a first time and via a first sensor of a first autonomous vehicle navigating inside of a first building at the target location, first sensor data about a first portion of a first room in the first building;
detect, via an onboard computing system for the first autonomous vehicle and based on the first sensor data, a first mudflow in the first portion;
determine, at an onboard computing system for the first autonomous vehicle and based on the first sensor data, that a first moisture content level for the first mudflow is less than a first threshold level; and
cause, via the onboard computing system and at a second time, a mud softener device installed on the first autonomous vehicle to dispense a first application of softener onto the first mudflow.
15 . The system of claim 14 , wherein the first mudflow has a first volume at the first time and a greater, second volume at the second time.
16 . The system of claim 14 , wherein the instructions further cause the processor to:
determine, at the onboard computing system, that the first mudflow is seeping below or through a wall; and
cause, via the onboard computing system, a robot effector arm of the first autonomous vehicle to tap a hole into the wall.
17 . The system of claim 14 , wherein the instructions further cause the processor to:
transmit, prior to the first time, a first signal identifying the target location from a remote computing system for a mud treatment service to the first autonomous vehicle, the first autonomous vehicle being stationed in a drone repository; and
cause, via the onboard computing system and in response to the first signal, the first autonomous vehicle to execute a path from the drone repository to the target location.
18 . The system of claim 17 , wherein the instructions further cause the processor to:
determine, via the onboard computing system, that an assessment of the first building has been completed;
cause, via the onboard computing system, the first autonomous vehicle to execute a return path from the target location to the drone repository;
transmit, after the first autonomous vehicle executes the return path, a second signal identifying the target location from the remote computing system for a mud removal service and navigation guidance to the first portion to a second autonomous vehicle, the second autonomous vehicle being stationed in the drone repository; and
cause, in response to the second signal, the second autonomous vehicle to execute a path from the drone repository to the first portion at the target location; causing a vacuum device for the second autonomous vehicle to remove the first mudflow.
19 . The system of claim 14 , wherein the instructions further cause the processor to:
determining a level of softener stored in a tank of the mud treatment device has fallen below a minimum level;
causing, via the onboard computing system, the first autonomous vehicle to execute a path from inside the first building to an exterior environment near the first building where a pool of water is present; and
refilling the tank with water available in the pool of water.
20 . The system of claim 14 , wherein the instructions further cause the processor to:
identify, based on the first sensor data, a difference between the first moisture content level and the first threshold level; and
calculate a first quantity of softener based on the difference, wherein the first application includes the first quantity.