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Roboat III: An autonomous surface vessel for urban transportation
Authors:Wei Wang  David Fernández-Gutiérrez  Rens Doornbusch  Joshua Jordan  Tixiao Shan  Pietro Leoni  Niklas Hagemann  Jonathan Klein Schiphorst  Fabio Duarte  Carlo Ratti  Daniela Rus
Affiliation:1. Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology, Cambridge, Massachusetts, USA;2. SENSEable City Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA;3. Amsterdam Institute for Advanced Metropolitan Solutions (AMS), Amsterdam, The Netherlands
Abstract:In this paper, we present our novel autonomous surface vessel platform, a full-scale Roboat for urban transportation. This 4-m-long Roboat is designed with six seats and can carry a payload of up to 1000 kg. Roboat has two main thrusters for cruising and two tunnel thrusters to accommodate docking and interconnectivity between Roboats. We build an adaptive nonlinear model predictive controller for trajectory tracking to account for payload changes while transporting passengers. We use a sparse directed graph to represent the canal topological map and then find the most time-efficient global path in a city-scale environment using the A * ${A}^{* }$ algorithm. We then employ a multiobjective algorithm's lexicographic search to generate an obstacle-free path using a point-cloud projected two-dimensional occupancy grid map. We also develop a docking mechanism to allow Roboat to “grasp” the docking station. Extensive experiments in Amsterdam waterways demonstrate that Roboat can (1) successfully track the optimal trajectories generated by the planner with varying numbers of passengers on board; (2) autonomously dock to the station without human intervention; (3) execute an autonomous water taxi task where it docks to pick up passengers, drive passengers to the destination while planning its path to avoid obstacles, and finally dock to drop off passengers.
Keywords:autonomous docking  autonomous navigation  autonomous surface vessels  model predictive control  urban transportation
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