Supervised Autonomous Locomotion and Manipulation for Disaster Response with a Centaur-Like Robot

Klamt, Tobias; Rodríguez, Diego; Schwarz, Max; Lenz, Christian; Pavlichenko, Dmytro; Droeschel, David; Behnke, Sven

doi:10.1109/iros.2018.8594509

Cited by 60 publications

(39 citation statements)

References 29 publications

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“…This wheeled quadrupedal robot uses a kinematic approach to drive and to overcome obstacles like stairs and steps. Recently, the Centauro robot [14]- [16] showed similar results over stepping stones, steps and first attempts to overcome stairs, while performing only slow static maneuvers.…”

Section: A Related Workmentioning

confidence: 95%

Keep Rollin’—Whole-Body Motion Control and Planning for Wheeled Quadrupedal Robots

Bjelonic

Bellicoso

Viragh

et al. 2019

IEEE Robot. Autom. Lett.

157

103

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We show dynamic locomotion strategies for wheeled quadrupedal robots, which combine the advantages of both walking and driving. The developed optimization framework tightly integrates the additional degrees of freedom introduced by the wheels. Our approach relies on a zero-moment point based motion optimization which continuously updates reference trajectories. The reference motions are tracked by a hierarchical wholebody controller which computes optimal generalized accelerations and contact forces by solving a sequence of prioritized tasks including the nonholonomic rolling constraints. Our approach has been tested on ANYmal, a quadrupedal robot that is fully torque-controlled including the non-steerable wheels attached to its legs. We conducted experiments on flat and inclined terrains as well as over steps, whereby we show that integrating the wheels into the motion control and planning framework results in intuitive motion trajectories, which enable more robust and dynamic locomotion compared to other wheeled-legged robots. Moreover, with a speed of 4 m/s and a reduction of the cost of transport by 83 % we prove the superiority of wheeled-legged robots compared to their legged counterparts.

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Section: A Related Workmentioning

confidence: 95%

Keep Rollin’—Whole-Body Motion Control and Planning for Wheeled Quadrupedal Robots

Bjelonic

Bellicoso

Viragh

et al. 2019

IEEE Robot. Autom. Lett.

157

103

View full text Add to dashboard Cite

show abstract

“…As a result, additional 2D camera images were displayed to the operator to visualize texture. Momaro served as a precursor to the Centauro robot [37], which extends the Momaro system in several directions, including immersive display of RGB-D data. However, the system is currently limited to displaying live data without aggregation.…”

Section: Related Workmentioning

confidence: 99%

A VR System for Immersive Teleoperation and Live Exploration with a Mobile Robot

Stotko

Krumpen

Schwarz

et al. 2019

2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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Applications like disaster management and industrial inspection often require experts to enter contaminated places. To circumvent the need for physical presence, it is desirable to generate a fully immersive individual live teleoperation experience. However, standard video-based approaches suffer from a limited degree of immersion and situation awareness due to the restriction to the camera view, which impacts the navigation. In this paper, we present a novel VR-based practical system for immersive robot teleoperation and scene exploration. While being operated through the scene, a robot captures RGB-D data that is streamed to a SLAM-based live multiclient telepresence system. Here, a global 3D model of the already captured scene parts is reconstructed and streamed to the individual remote user clients where the rendering for e.g. head-mounted display devices (HMDs) is performed. We introduce a novel lightweight robot client component which transmits robot-specific data and enables a quick integration into existing robotic systems. This way, in contrast to firstperson exploration systems, the operators can explore and navigate in the remote site completely independent of the current position and view of the capturing robot, complementing traditional input devices for teleoperation. We provide a proofof-concept implementation and demonstrate the capabilities as well as the performance of our system regarding interactive object measurements and bandwidth-efficient data streaming and visualization. Furthermore, we show its benefits over purely video-based teleoperation in a user study revealing a higher degree of situation awareness and a more precise navigation in challenging environments.

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“…We employed the 3D version of AVINs to plan omnidirectional driving locomotion while considering the robot footprint. An example platform is the quadrupedal disaster response robot Centauro [14] whose legs end in 360°steerable, active wheels ( Fig. 10).…”

Section: Planning 3d Locomotion With Footprint Considerationmentioning

confidence: 99%

Value Iteration Networks on Multiple Levels of Abstraction

Schleich¹,

Klamt²,

Behnke³

2019

Robotics: Science and Systems XV

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Learning-based methods are promising to plan robot motion without performing extensive search, which is needed by many non-learning approaches. Recently, Value Iteration Networks (VINs) received much interest since-in contrast to standard CNN-based architectures-they learn goal-directed behaviors which generalize well to unseen domains. However, VINs are restricted to small and low-dimensional domains, limiting their applicability to real-world planning problems.To address this issue, we propose to extend VINs to representations with multiple levels of abstraction. While the vicinity of the robot is represented in sufficient detail, the representation gets spatially coarser with increasing distance from the robot. The information loss caused by the decreasing resolution is compensated by increasing the number of features representing a cell. We show that our approach is capable of solving significantly larger 2D grid world planning tasks than the original VIN implementation. In contrast to a multiresolution coarse-to-fine VIN implementation which does not employ additional descriptive features, our approach is capable of solving challenging environments, which demonstrates that the proposed method learns to encode useful information in the additional features. As an application for solving real-world planning tasks, we successfully employ our method to plan omnidirectional driving for a search-and-rescue robot in cluttered terrain.

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Supervised Autonomous Locomotion and Manipulation for Disaster Response with a Centaur-Like Robot

Cited by 60 publications

References 29 publications

Keep Rollin’—Whole-Body Motion Control and Planning for Wheeled Quadrupedal Robots

Keep Rollin’—Whole-Body Motion Control and Planning for Wheeled Quadrupedal Robots

A VR System for Immersive Teleoperation and Live Exploration with a Mobile Robot

Value Iteration Networks on Multiple Levels of Abstraction

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