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Duberg, Daniel
Publications (3 of 3) Show all publications
Selin, M., Tiger, M., Duberg, D., Heintz, F. & Jensfelt, P. (2019). Efficient Autonomous Exploration Planning of Large-Scale 3-D Environments. IEEE Robotics and Automation Letters, 4(2), 1699-1706
Open this publication in new window or tab >>Efficient Autonomous Exploration Planning of Large-Scale 3-D Environments
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2019 (English)In: IEEE Robotics and Automation Letters, ISSN 2377-3766, E-ISSN 1949-3045, Vol. 4, no 2, p. 1699-1706Article in journal (Refereed) Published
Abstract [en]

Exploration is an important aspect of robotics, whether it is for mapping, rescue missions, or path planning in an unknown environment. Frontier Exploration planning (FEP) and Receding Horizon Next-Best-View planning (RH-NBVP) are two different approaches with different strengths and weaknesses. FEP explores a large environment consisting of separate regions with ease, but is slow at reaching full exploration due to moving back and forth between regions. RH-NBVP shows great potential and efficiently explores individual regions, but has the disadvantage that it can get stuck in large environments not exploring all regions. In this letter, we present a method that combines both approaches, with FEP as a global exploration planner and RH-NBVP for local exploration. We also present techniques to estimate potential information gain faster, to cache previously estimated gains and to exploit these to efficiently estimate new queries.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2019
Keywords
Search and rescue robots, motion and path planning, mapping
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
urn:nbn:se:kth:diva-246228 (URN)10.1109/LRA.2019.2897343 (DOI)000459538100069 ()2-s2.0-85063311333 (Scopus ID)
Note

QC 20190404

Available from: 2019-04-04 Created: 2019-04-04 Last updated: 2019-04-04Bibliographically approved
Barbosa, F. S., Duberg, D., Jensfelt, P. & Tumova, J. (2019). Guiding Autonomous Exploration with Signal Temporal Logic. IEEE Robotics and Automation Letters, 4(4), 3332-3339
Open this publication in new window or tab >>Guiding Autonomous Exploration with Signal Temporal Logic
2019 (English)In: IEEE Robotics and Automation Letters, ISSN 2377-3766, E-ISSN 1949-3045, Vol. 4, no 4, p. 3332-3339Article in journal (Refereed) Published
Abstract [en]

Algorithms for autonomous robotic exploration usually focus on optimizing time and coverage, often in a greedy fashion. However, obstacle inflation is conservative and might limit mapping capabilities and even prevent the robot from moving through narrow, important places. This letter proposes a method to influence the manner the robot moves in the environment by taking into consideration a user-defined spatial preference formulated in a fragment of signal temporal logic (STL). We propose to guide the motion planning toward minimizing the violation of such preference through a cost function that integrates the quantitative semantics, i.e., robustness of STL. To demonstrate the effectiveness of the proposed approach, we integrate it into the autonomous exploration planner (AEP). Results from simulations and real-world experiments are presented, highlighting the benefits of our approach.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2019
Keywords
Mapping, motion and path planning, formal methods in robotics and automation, search and rescue robots
National Category
Robotics
Identifiers
urn:nbn:se:kth:diva-255721 (URN)10.1109/LRA.2019.2926669 (DOI)000476791300029 ()2-s2.0-85069437912 (Scopus ID)
Note

QC 20190813

Available from: 2019-08-13 Created: 2019-08-13 Last updated: 2019-08-13Bibliographically approved
Duberg, D. & Jensfelt, P. (2018). The Obstacle-restriction Method for Tele-operation of Unmanned Aerial Vehicles with Restricted Motion. In: 2018 15TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION, ROBOTICS AND VISION (ICARCV): . Paper presented at 15th International Conference on Control, Automation, Robotics and Vision (ICARCV), NOV 18-21, 2018, Singapore, SINGAPORE (pp. 266-273). IEEE
Open this publication in new window or tab >>The Obstacle-restriction Method for Tele-operation of Unmanned Aerial Vehicles with Restricted Motion
2018 (English)In: 2018 15TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION, ROBOTICS AND VISION (ICARCV), IEEE , 2018, p. 266-273Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents a collision avoidance method for tele-operated unmanned aerial vehicles (UAVs). The method is designed to assist the operator at all times, such that the operator can focus solely on the main objectives instead of avoiding obstacles. We restrict the altitude to be fixed in a three dimensional environment to simplify the control and operation of the UAV. The method contributes a number of desired properties not found in other collision avoidance systems for tele-operated UAVs. Our method i) can handle situations where there is no input from the user by actively stopping and proceeding to avoid obstacles, ii) allows the operator to slide between prioritizing staying away from objects and getting close to them in a safe way when so required, and iii) provides for intuitive control by not deviating too far from the control input of the operator. We demonstrate the effectiveness of the method in real world experiments with a physical hexacopter in different indoor scenarios. We also present simulation results where we compare controlling the UAV with and without our method activated.

Place, publisher, year, edition, pages
IEEE, 2018
Series
International Conference on Control Automation Robotics and Vision, ISSN 2474-2953
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
urn:nbn:se:kth:diva-246315 (URN)000459847700046 ()978-1-5386-9582-1 (ISBN)
Conference
15th International Conference on Control, Automation, Robotics and Vision (ICARCV), NOV 18-21, 2018, Singapore, SINGAPORE
Note

QC 20190319

Available from: 2019-03-19 Created: 2019-03-19 Last updated: 2019-05-13Bibliographically approved
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