Synthetic 2D LIDAR for precise vehicle localization in 3D urban environment

Chong, Zhuang Jie; Qin, Bo; Bandyopadhyay, Tirthankar; Ang, Marcelo H.; Frazzoli, Emilio; Rus, Daniela

doi:10.1109/icra.2013.6630777

Cited by 91 publications

(53 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…self-contained versus reliance on infrastructure), the different approaches vary primarily on their level of redundancy. In terms of localization, the following combinations have been used in conjunction with odometry: infrastructure magnets [8]; LIDAR only [10]; LIDAR and camera [11]; LIDAR, camera, and DGPS [12]. In terms of obstacle detection, the following combinations have been used in conjunction with LIDAR: LIDAR only [6]; ultrasonic [8], [13]; camera, radar, and infrared sensors [14].…”

Section: Related Workmentioning

confidence: 99%

Autonomous golf cars for public trial of mobility-on-demand service

Pendleton

Uthaicharoenpong

Chong

et al. 2015

2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

View full text Add to dashboard Cite

Abstract-We detail the design of autonomous golf cars which were used in public trials in Singapore's Chinese and Japanese Gardens, for the purpose of raising public awareness and gaining user acceptance of autonomous vehicles. The golf cars were designed to be robust, reliable, and safe, while operating under prolonged durations. Considerations that went in to the overall system design included the fact that any member of the public had to not only be able to easily use the system, but to also not have the option to use the system in an unintended manner. This paper details the hardware and software components of the golf cars with these considerations, and also how the booking system and mission planner facilitated users to book for a golf car from any of ten stations within the gardens. We show that the vehicles performed robustly throughout the prolonged operations with a small localization variance, and that users were very receptive from the user survey results.

show abstract

Section: Related Workmentioning

confidence: 99%

Autonomous golf cars for public trial of mobility-on-demand service

Pendleton

Uthaicharoenpong

Chong

et al. 2015

2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

View full text Add to dashboard Cite

show abstract

“…One SICK LMS 151 LIDAR is mounted at a tilted down angle, and the data returned is fused with odometry readings to achieve mapping and localization by the methods described in [3]. The SICK LMS151 scans at 50 Hz over 270 degrees with the range of up to 50 meters, and resolution of 0.5 degree.…”

Section: B Sensorsmentioning

confidence: 99%

“…Our localization system mainly consists of two parts, 3D perception to extract key feature points, and 2D localization to solve the localization problem on the horizontal plane. Synthetic LIDAR, a specific sensor model [3], serves as a bridge to connect the 3D world and the 2D virtual plane.…”

Section: F Softwarementioning

confidence: 99%

“…• Mapping and localization in 3D environment with synthetic 2D LIDAR [3], [4] • Dynamic replanning for online obstacle avoidance [5] • Moving obstacles detection and tracking [6] • Intuitive web-based booking system [7] The functionality of the service was demonstrated in an uncontrolled environment open to real pedestrian and vehicular traffic. It is shown that while the car can operate at higher speeds on the road, the golf car has the flexibility of operating in pedestrian areas where cars are not allowed, thereby expanding the area coverage of the MoD service.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Autonomous personal mobility scooter for multi-class mobility-on-demand service

Andersen

Eng

Leong

et al. 2016

2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC)

View full text Add to dashboard Cite

Abstract-In this paper, we describe the design and development of an autonomous personal mobility scooter that was used in public trials during the 2016 MIT Open House, for the purpose of raising public awareness and interest about autonomous vehicles. The scooter is intended to work cooperatively with other classes of autonomous vehicles such as road cars and golf cars to improve the efficacy of Mobilityon-Demand transportation solutions. The scooter is designed to be robust, reliable, and safe, while operating under prolonged durations. The flexibility in fleet expansion is shown by replicating the system architecture and sensor package that has been previously implemented in the road car and golf cars. We show that the vehicle performed robustly with small localization variance. A survey of the users shows that the public is very receptive to the concept of the autonomous personal mobility device.

show abstract

“…There are some successful research efforts in this field, and even it has been turned into commercial products such as Velodyne Lidar [1]. Integration of laser scanners or 3D LiDar sensor to build a 3D map of the environment is reported in [3], [11], [18], [21]. Their proposed 3D mapping systems integrated on mobile vehicle can work on a large scale of the environment, but they are not suitable for a device with normally worm such as our shoe in this paper.…”

Section: Introductionmentioning

confidence: 99%

Development of a Smart Shoe for Building a Real-Time 3D Map

Nguyen¹,

La²

2015

Proceedings of the International Symposium on Automation and Robotics in Construction (IAARC)

View full text Add to dashboard Cite

Abstract-Three dimensional (3D) mapping of environments has gained significant research interest over the last decades because of its important need for environmental modeling and monitoring. There are many successful research efforts in this field, and even it has been turned into commercial products such as Velodyne Lidar [1]. However, due to natural localization challenges, not much research for 3D mapping wearable sensor devices has been successfully reported. In this paper, we are interested in building a smart and wearable shoe which integrates multiple laser scanners and an inertial measurement unit (IMU) to build a 3D map of the environments. The proposed Smart Shoe can collect data and build a real-time 3D map during human walking. Such a smart shoe can support disabled people (blind people) to easily navigate and avoid obstacles in the environment. Additionally, this shoe can help firefighters quickly model and recognize objects in the fired and dark smoke buildings where the cameras may not be useful. The developed localization algorithm using IMU can output a smooth and accurate pose and trajectory of the human walking. This key importance of the shoe localization enables 3D mapping successfully while minimizing data registration error from the laser point cloud.

show abstract

Synthetic 2D LIDAR for precise vehicle localization in 3D urban environment

Cited by 91 publications

References 25 publications

Autonomous golf cars for public trial of mobility-on-demand service

Autonomous golf cars for public trial of mobility-on-demand service

Autonomous personal mobility scooter for multi-class mobility-on-demand service

Development of a Smart Shoe for Building a Real-Time 3D Map

Contact Info

Product

Resources

About