Autonomous Delivery robot/vehicle
Aim
To enforce social distancing by delivering essentials to customers and also to save doctors attending to corona patients
Background: In these desperate times, where the world reels under the corona crisis, social distancing has become really important. To enforce this, most countries are following a total lockdown policy. However, people still need certain essential items for which they have to leave the security of their house which poses a great risk to their health.
OPPORTUNITYA large number of essential items like groceries and medicines can be delivered to our doorstep. However, mobilising human delivery agents puts them at the risk of contracting the dreaded disease.
Also, it would be difficult to supply every other household given the availability of delivery agents.
Materials needed
- Husky Lens
- ESP32 development board
- AIThinker A9G module
- Geared DC motors with encoder
- 3D printed chassis
- RasPi Cam V2
- 3d printed robotic arms
- Charger module
- LiPo battery
- Buck convertor
- SIM card
- Servo motors
- SD/eMMc card and module
- PCB thru hole
- Connecting wires
IDEAWhat I propose is to build an autonomous robot that would use the Husky Lens for path traversal. It would collect essentials from shopkeepers and deliver them to customers.
How would the bot know which product to deliver to whom? For that each order would be issued an ID by the backend web application(Node-Red) and updated OTA on to the bot which would have a GPRS module for this communication. A mobile application would also be made for getting orders. The app would generate AruCo markers encoding a particular order ID which would appear on the shopkeeper`s and the buyer`s copy of the application, The Husky Lens can easily decipher the marker which the buyer and seller would place in front of the camera for receiving the corect package. This would ensure end to end security and in the greater context, a safer society.
The same bot can also be used inside a quarantine centre or a hospital for delivering medicines and checking the patient`s condition putting medical staff to lower risk and compensate for the lack in manpower is faced by hospitals. In indoor environments, black lines can be drawn on the floor with generic coloured tape that the Husky Lens can easily detect and the patient bed can have an AruCo marker to determine what medicine needs to be delivered or what checkup is to be done.
ArUco markers are the way to go
IMPLEMENTATION• For indoor environments, an ESP32 can be the controller board as OTA updates over WiFi would be much easier
• For delivery agent bots, I propose a GPRS module to communicate with the bot which can use an ESP32 as the main controller.
• The Husky Lens would be mounted with camera facing front on a hobby servo axle for 3D Mapping of the surroundings
• A GPS Module (Ublox Neo-8M) would give the bot a rough estimate of its location to within 6m range.
• A generic micro-SD-card module interfaced with the ESP32 would serve as cache memory to keep track of the bot`s location by creating a local 2D map of the surroundings as soon as the bot loses GPS connectivity or is leaving a main road to reach a location in a lane.
• The 2D mapping algorithm would still be used in indoor environments.
3D mapping of lanes
Challenges that will be faced:• The algorithms on the Husky Lens are not capable of lane detection and it has to be programmed further
• The application needs to be developed and I frankly do not have much idea about app development.
• Deliveries in narrow lanes with undulating terrains would be difficult to traverse and the mechanical design of the bot would be a challenge
• GPS and mobile network would not be accessible from all locations, especially with high-rise apartments around the bot
If you have any suggestions please let me know in the comments below.
Update:
Got a basic version of the web-app up and running. It is posted on the IOT appstore. The nodes seem to be working fine and the MQTT message latency is acceptable.
The next task is to tinker the Husky Lens.
Stay tuned.
Meanwhile, I have thought more on the smart hospital idea. Here it is.
To prevent doctors attending to corona victims from infection, I propose an autonomous ground robot that can be given instructions remotely through a mobile application to perform treatment. The bot would perform tasks like giving food and medicines, cleaning, monitoring of biomedical equipment and trigger notifications to medical staff in case of an emergency. The data from various biomedical equipment would be stored on the cloud and can be used for drug discovery or better treatment.
Doctors would have the option to instruct the bot wirelessly through WiFi or in hospitals where that is not available through mobile internet. The bot would also have a camera for the doctor to check the patients’ condition and various medical modules can be mounted on the bot to do complex tasks like controlling biomedical equipment, collecting blood samples and injections.
The application would make managing many patients easy and help in taking life-saving decisions remotely if a doctor isn’t available on the spot. If the doctor responsible for treating a patient cannot act upon being notified by the bot, it would quickly connect to the vast network of competent doctors enrolled on the platform(much like Ola/Uber) to take over, thus saving many unnecassirily lost lives.
For the bot to traverse, the hospital floor would be marked with black lines which the bot would follow to reach the desired patient.
The patient beds would be equipped with WiFi and cellular modules to send data directly to the application and hence, the doctors.
The product addresses all the key problems in hospitals today. Doctors are much safer, less number of doctors are required, patient management is better and many life-saving decisions can be taken remotely.
The cost of making a bot is less than Rs.8000 and the modules attached to the bed cost a mere Rs.400. Very cheap indeed. We cannot emphasise more on how many doctors this technology will save. All it needs is some support.
Thank you.
Don’t know about HuskyLens? Have a look.
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