Planning and Control for Autonomous Excavation

Jud, Dominic; Hottiger, Gabriel; Leemann, Philipp; Hutter, Marco

doi:10.1109/lra.2017.2721551

Cited by 80 publications

(49 citation statements)

References 16 publications

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“…The results shown in this article are compared to our previous work in simulation [14], Shao et al [26] and Maeda et al [11]. In our simulation work, a mean error of 0.035m and 0.044m for two different shapes was achieved.…”

Section: Resultssupporting

confidence: 49%

“…7. First, a suitable point of attack for digging, using the excavation planner proposed in previous work [14], is found. The trajectory planner, as shown in Section IV, subsequently plans an environment collision-free trajectory from the current location of the bucket to the excavation point.…”

Section: Autonomous Excavationmentioning

confidence: 99%

“…In our previous work in simulation [14], the first step was to roughly excavate the entire trench and, in a last step, to refine it to achieve a precise shape. Due to splitting these actions into two separate parts, the excavator had to go to the start of the trench after finishing rough excavation.…”

Section: Autonomous Excavationmentioning

confidence: 99%

“…1. It builds upon our previous work in simulation showing a planning and control approach [14] consisting of force trajectory based dig cycles which reliably fill the bucket without any knowledge about the soil properties. We present the hardware extensions and modifications that are necessary to facilitate these force controlled dig cycles on a real machine, a robust excavation mapping approach based on fusing proprioceptive and exteroceptive mapping, trajectory planning that leverages the excavation map, control for safe and accurate operation of the arm and an improved state machine to adapt to the differences between simulation and real hardware.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Autonomous Free-Form Trenching Using a Walking Excavator

Jud

Leemann

Kerscher

et al. 2019

IEEE Robot. Autom. Lett.

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This article shows accurate and autonomous creation of free-form trenches using a walking excavator. We present hardware extensions and modifications for full automation, a mapping approach specifically tailored to excavation, environment collision-free trajectory planning on these maps, an arm controller aware of various limits and an improved state machine that enables the execution on real hardware. Furthermore, previous work about excavation planning and the design of a single soil-independent dig cycle is extended and transferred from simulation to hardware. The entire system is tested on a foursegment, piecewise-planar trench and a free-form curved trench. Both shapes were successfully excavated with unprecedented accuracy.

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Section: Resultssupporting

confidence: 49%

Section: Autonomous Excavationmentioning

confidence: 99%

Section: Autonomous Excavationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Autonomous Free-Form Trenching Using a Walking Excavator

Jud

Leemann

Kerscher

et al. 2019

IEEE Robot. Autom. Lett.

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“…No.19-00320 [DOI:10.1299/transjsme.19-00320] 6 ( 2015) / (Jud et al, 2017) Fig. 1 Three types of digging for soft, hard and the mixture of soft and hard soils.…”

mentioning

confidence: 99%

Semi-autonomous control of excavation using model of human operation and state estimation via Extended Kalman Filter

Okada

Okamoto

Masuya

2020

Transactions of the JSME (In Japanese)

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For robotic teleoperation, semi-autonomous control, i.e. autonomous control allowing human interposition will be an effective way overcoming delay of electrical communication and emergency operation. We have proposed semiautonomous control method focusing on excavation in teleoperation environments. In the method, a model of human operation is designed and human internal state is estimated by Extended Kalman Filter. In this paper, experimental evaluations are conducted and reported about "Digging" process. A human skill of excavation is modeled by an attractorbased dynamics embedding shallow and deep digging trajectories for soft and hard soil, respectively. An index parameter is changed based on the load of the bucket, and a seamless motion transition is realized satisfying the restriction by setting a threshold. Moreover, by adding a human operation to the autonomy, the proposed method will cope with the emergency, which is experimentally evaluated.

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