Overview of team ViGIR's approach to the Virtual Robotics Challenge

Kohlbrecher, Stefan; Conner, David C.; Romay, Alberto; Bacim, Felipe; Bowman, Doug A.; Stryk, Oskar von

doi:10.1109/ssrr.2013.6719382

Cited by 9 publications

(3 citation statements)

References 4 publications

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“…Team ViGIR is a cooperation between research groups in Germany and other research institutions in the USA. After our participation in the three main events, the Virtual Robotics Challenge (VRC) [19] in June 2013, the DRC Trials in December 2013 [20] and the very recent DRC Finals in June 2015, we are confident that the previously proposed object template manipulation approach can be used to perform manipulation tasks in unstructured environments using human supervision of a remote semi-autonomous robot. This paper adds to our previous contribution an approach to perform versatile robotic manipulation tasks in remote unstructured environments based on object templates.…”

Section: B Overviewmentioning

confidence: 96%

Achieving versatile manipulation tasks with unknown objects by supervised humanoid robots based on object templates

Romay

Kohlbrecher

Conner

et al. 2015

2015 IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids)

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The investigations of this paper are motivated by the scenario of a supervised semi-autonomous humanoid robot entering a mainly unknown, potentially degraded human environment to perform highly diverse disaster recovery tasks. For this purpose, the robot must be enabled to use any object it can find in the environment as tool for achieving its current manipulation task. This requires the use of potential unknown objects as well as known objects for new purposes (e.g. using a drill as a hammer). A recently proposed object template manipulation approach is extended to provide a semi-autonomous humanoid robot assisted by a remote human supervisor with the versatility needed to utilize objects in the described manner applying affordances [1] from other previously known objects. For an Atlas humanoid robot it is demonstrated how using a small set of such object templates with well defined affordances can be used to solve manipulation tasks using new unknown objects.

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Section: B Overviewmentioning

confidence: 96%

Achieving versatile manipulation tasks with unknown objects by supervised humanoid robots based on object templates

Romay

Kohlbrecher

Conner

et al. 2015

2015 IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids)

Self Cite

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“…Kohlbrecher et al [15] had developed open-loop key frame-based quadrupedal locomotion which was used during the rough terrain task and whenever the robot had fallen. Team ViGIRs approach was satisfying on rough terrain but had many limitations in narrow spaces and it reduced the Atlas workspace.…”

Section: Related Workmentioning

confidence: 99%

Stability Controller on the Atlas Robot Example

Wasielica

2017

PAR

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“…However, they were not able to complete their missions due to uneven terrain, including slopes, stairs, and ladders. After this failure, the Defense Advanced Research Project Agency (DARPA) in 2012 launched a robotics challenge project requesting robots to perform tasks specified particularly for disaster circumstances, and Team ViGIR realized those tasks through computer simulations in 2013 [1]. Feng S. et al generated walking paths considering the center of mass (CoM) and performed simulations and experiments of biped walking and ladder climbing using the humanoid robot ATLAS (Boston Dynamics Co., Boston, MA, USA) [2].…”

Section: Introductionmentioning

confidence: 99%

Vision-Guided Six-Legged Walking of Little Crabster Using a Kinect Sensor

et al. 2022

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A conventional blind walking algorithm has low walking stability on uneven terrain because a robot cannot rapidly respond to height changes of the ground due to limited information from foot force sensors. In order to cope with rough terrain, it is essential to obtain 3D ground information. Therefore, this paper proposes a vision-guided six-legged walking algorithm for stable walking on uneven terrain. We obtained noise-filtered 3D ground information by using a Kinect sensor and experimentally derived coordinate transformation information between the Kinect sensor and robot body. While generating landing positions of the six feet from the predefined walking parameters, the proposed algorithm modifies the landing positions in terms of reliability and safety using the obtained 3D ground information. For continuous walking, we also propose a ground merging algorithm and successfully validate the performance of the proposed algorithms through walking experiments on a treadmill with obstacles.

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Overview of team ViGIR's approach to the Virtual Robotics Challenge

Cited by 9 publications

References 4 publications

Achieving versatile manipulation tasks with unknown objects by supervised humanoid robots based on object templates

Achieving versatile manipulation tasks with unknown objects by supervised humanoid robots based on object templates

Stability Controller on the Atlas Robot Example

Vision-Guided Six-Legged Walking of Little Crabster Using a Kinect Sensor

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