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

Abstract

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.

Golf cart prototype development and navigation simulation using ROS and Gazebo

“…Gazebo 4 is an integrated with ROS graphical engine, which simulates physics, builds a 3D robot model using its URDF description 5 , and then allows running vehicle control algorithms in a developed environment. To control AGC model we used ROS Indigo [7] software, where we have modified the basic 4 Gazebo is 3D robot simulator: www.gazebosim.org 5 URDF is a Unified Robot Description Format, which is an XML format for robot model representing within ROS.…”

“…While large car manufacturers expand testing of autonomous cars, different universities research teams concentrate on specialized vehicles automation, for example, such as self-driving golf carts [2][3][4][5].…”

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

“…This new personal mobility vehicle class is small enough to travel even within the insides of buildings and perform tight manoeuvres in dense crowds, though it is also capable of outdoor operation. We have discussed various different localization and perception approaches in our previous work [8], with different environmental factors, sensor packages and redundancies involved. With the personal mobility vehicle, our approach to achieving autonomous navigation continues to be selfcontained rather than relying on external infrastructure, so that it can be deployed in different environments, such as indoors and urban areas, where GPS signal is not strong enough to achieve decimetre level localization accuracy.…”

“…The scooter also has an advantage when operating in crowded indoor environment, as it is easier to manoeuvre the smaller vehicle within dense crowds. 2) Adapting our mapping, localization, perception, and planning capabilities to the scooter platform: The personal mobility scooter is developed with similar sensors and software packages to what has been implemented in our road car and golf cars [8], maximizing code re-usability and demonstrating the flexibility of our software architecture. 3) Extensive experiments and user surveys: The scooter was showcased during MIT's open house to raise public awareness on autonomous driving technologies, 99 trips were recorded, with 73 m of distance covered per trip, totalling 7.23 km travelled in autonomous mode.…”

Adaptive path tracking for unmanned ground vehicle

“…UGV offer potential for additional safety, increasing productivity, greater accessibility, better road efficiency and positive impact to the environment [1]. Besides, UGV have been applied to various kinds of fields.…”