Problem Description:
Litter is a major problem worldwide. Billions of dollars are spent each year to clean up litter. For example, the state of Arizona spends around $3M a year to pick-up litter on its freeways. A few of the most commonly found types of litter include soda cans, water bottles, paper, and cigarette butts. Littering of these items happens all too often since they are small and people don’t feel the direct detrimental effects of littering; i.e., the tragedy of the commons.
Although litter is a broad issue that affects many locales, the problem our project focuses on is litter in campus-like environments. This is an important problem universities must deal with. If left unchecked, it can tarnish a university’s brand, resulting in fewer students desiring to study at the university and fewer professors wanting to work at the university. It’s a problem that is currently addressed using human workers. Our team believes the specific use-case of litter pick-up in campus-like environments is not well-suited to human labor and should be addressed with a robotic solution.
While human workers are well-suited to picking up litter in areas that are densely packed with litter, such as after a festival or sporting event, the economics change drastically when a human worker has to patrol large areas that have few pieces of litter. Our team believes a robotic solution is better-suited to this problem, as it can work continuously without getting fatigued. Furthermore, a robotic solution can be more economical as the major cost of such a solution is fixed rather than being a recurring cost.
Use Case
Carnegie Mellon University students are busy, hard-working students. In the pursuit of trying to meet different deadlines, CMU students often consume energy drinks in cans and bottles to keep them powered throughout the day. Most students unintentionally “forget” their soda cans on The Cut. This causes a litter issue for the university and tarnishes CMU’s pristine image.
Currently, this issue is being handled by CMU’s custodial staff by physically picking up litter from The Cut periodically. Doing this only keeps The Cut clean for short periods of time before becoming littered again. This puts too much strain on the already overworked custodial staff. To solve this problem we introduce Mell-E (Mobile Electromechanical Litter Locator – Earthspace).
To operate Mell-E, CMU’s custodial staff would simply place Mell-E within the vicinity of The Cut. Then by opening the companion app on an Android phone, the custodial staff will define the cleaning boundary areas. Mell-E will then wake up, receive its boundary constraints and start patrolling.
Based on an efficient patrol plan, Mell-E will autonomously patrol The Cut area. As it patrols, Mell-E is continuously scanning its surroundings for litter. Once Mell-E finds an object it believes is litter, it will move to the litter and identify the class of litter. It will then pick-up the litter and store it in its carry on bin. This process will be repeated until: (a) the whole boundary is covered, (b) Mell-E’s litter storage bin is full, (c) Mell-E runs out of power or (d) it’s called back by the custodial staff. By doing this, Mell-E will ensure a clean and litter free Cut.
Unlike human workers, Mell-E does not get tired of doing this repetitive task and is more than happy to keep The Cut clean. The custodial staff will no longer need to keep cleaning The Cut every hour, while the campus remains clean, allowing CMU to hold its pristine reputation as a top-class clean university.
Sources:
California Towns Spend $428 Million a Year Cleaning Up Polluted Beaches