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Valencia, Rafael
Publications (2 of 2) Show all publications
David, J., Valencia, R., Philippsen, R. & Iagnemma, K. (2017). Local Path Optimizer for an Autonomous Truck in a Harbour Scenario. In: : . Paper presented at 11th Conference on Field and Service Robotics (FSR), Zürich, Switzerland, 12-15 September, 2017.
Open this publication in new window or tab >>Local Path Optimizer for an Autonomous Truck in a Harbour Scenario
2017 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Recently, functional gradient algorithms like CHOMP have been very successful in producing locally optimal motion plans for articulated robots. In this paper, we have adapted CHOMP to work with a non-holonomic vehicle such as an autonomous truck with a single trailer and a differential drive robot. An extended CHOMP with rolling constraints have been implemented on both of these setup which yielded feasible curvatures. This paper details the experimental integration of the extended CHOMP motion planner with the sensor fusion and control system of an autonomous Volvo FH-16 truck. It also explains the experiments conducted on the differential-drive robot. Initial experimental investigations and results conducted in a real-world environment show that CHOMP can produce smooth and collision-free trajectories for mobile robots and vehicles as well. In conclusion, this paper discusses the feasibility of employing CHOMP to mobile robots.

Keywords
robotics
National Category
Robotics Computer Vision and Robotics (Autonomous Systems)
Identifiers
urn:nbn:se:hh:diva-34850 (URN)
Conference
11th Conference on Field and Service Robotics (FSR), Zürich, Switzerland, 12-15 September, 2017
Projects
Cargo-ANTs
Funder
EU, FP7, Seventh Framework Programme, FP7-605598
Available from: 2017-08-31 Created: 2017-08-31 Last updated: 2019-01-29Bibliographically approved
David, J., Valencia, R. & Iagnemma, K. (2016). Task Assignment and Trajectory Planning in Dynamic environments for Multiple Vehicles. In: : . Paper presented at RSS 2016 Workshop on Task and Motion Planning, Ann Arbor, Michigan, USA, June 19, 2016.
Open this publication in new window or tab >>Task Assignment and Trajectory Planning in Dynamic environments for Multiple Vehicles
2016 (English)Conference paper, Published paper (Refereed)
Abstract [en]

We consider the problem of finding collision-free trajectories for a fleet of automated guided vehicles (AGVs) working in ship ports and freight terminals. Our solution computes collision-free trajectories for a fleet of AGVs to pick up one or more containers and transport it to a given goal without colliding with other AGVs and obstacles. We propose an integrated framework for solving the goal assignment and trajectory planning problem minimizing the maximum cost overall vehicle trajectories using the classical Hungarian algorithm.To deal with the dynamics in the environment, we refine our final trajectories with CHOMP (Covariant Hamiltonianoptimization for motion planning) in order to trade off between path smoothness and dynamic obstacle avoidance.

Keywords
Multi-robot, task assignment, path planner
National Category
Robotics
Identifiers
urn:nbn:se:hh:diva-31738 (URN)
Conference
RSS 2016 Workshop on Task and Motion Planning, Ann Arbor, Michigan, USA, June 19, 2016
Projects
CargoAnts
Funder
EU, FP7, Seventh Framework Programme, 605598
Available from: 2016-08-10 Created: 2016-08-10 Last updated: 2018-03-22Bibliographically approved
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