Name
Abstract | ||
|---|---|---|
Despite the technical success of existing assistive technologies, for example, electric wheelchairs and scooters, they are still far from effective enough in helping the blind and elderly navigate to their destinations in a hassle-free manner. Riders often face challenges in driving scooters in some indoor and crowded places, especially on sidewalks with numerous obstacles and other pedestrians. People with certain disabilities, such as the blind, are often unable to drive their scooters well enough. In this paper, we propose to improve the safety and autonomy of the navigation by designing a cutting-edge autonomous scooter, which allows people with mobility challenges to navigate independently and safely in possibly unfamiliar surroundings. We focus on the localization and navigation challenges for the autonomous scooter where the current location, maps, and nearby obstacles are unknown. Solving these challenges will enable the scooter to both travel within buildings and perform tight maneuvers in densely crowds automatically. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/ICCC.2018.00020 | 2018 IEEE International Conference on Cognitive Computing (ICCC) |
Keywords | Field | DocType |
Autonomous system,Sensor fusion,Scooter,SLAM | Electric wheelchairs,Crowds,Computer science,Autonomy,Human–computer interaction,Simultaneous localization and mapping | Conference |
ISBN | Citations | PageRank |
978-1-5386-7242-6 | 0 | 0.34 |
References | Authors | |
2 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rajath Swaroop Mulky | 1 | 0 | 0.34 |
| Supradeep Koganti | 2 | 0 | 0.34 |
| Sneha Shahi | 3 | 0 | 0.68 |
| Kaikai Liu | 4 | 190 | 20.37 |