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DFKI- Labor Bremen & Universität Bremen Forschungsgruppe Robotik PowerPoint Presentation
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DFKI- Labor Bremen & Universität Bremen Forschungsgruppe Robotik

DFKI- Labor Bremen & Universität Bremen Forschungsgruppe Robotik

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DFKI- Labor Bremen & Universität Bremen Forschungsgruppe Robotik

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  1. Asguard: A Hybrid Legged-Wheel Security and SAR-Robot Using Bio-Inspired Locomotion for Rough Terrain DFKI- Labor Bremen & Universität Bremen Forschungsgruppe Robotik Director: Prof. Dr. Frank Kirchner www.dfki.de/robotics robotics@dfki.de

  2. Overview • Motivation for Legged-Wheel Locomotion • The Physical Robot Asguard • CPG-based Locomotion Control • Adaptive Proprioceptive Control • Results

  3. Asguard Hybrid Legged-Wheel Robot ARAMIES Walking Robot Motivation for Legged-Wheel Locomotion • Wheels are most suitable for high velocities • Legs are suitable to overcome obstacles and climb stairs • Many robotic applications in security and SAR fields need both • Combining the advantages of wheeled and legged locomotion in one system

  4. The Physical Robot Asguard (I) • Five compliant legs are mounted around an axis shaft • Elastic foot tips reduce shock for high velocities • Elastic spinal column (passive) for ground adaptation Schematic of stair climbing Shock absorbing foot tip Asguard compliant leg

  5. The Physical Robot Asguard (II) PC 104 Onboard Computer Custom FPGA Sensor/Motor Board Modular Camera Section (Zoom / IR) 95 cm LiPoly Battery 30V/10Ah 4x Faulhaber 24V DC 83W 50 cm Weight: 11.5 kg

  6. CPG Based Locomotion Control (I) • Central Pattern Generators in biological systems are self-sustaining neural circuits which produce rhythmic oscillations. • These patterns can be found in biological systems (from insects to humans), where rhythmic actuation is required (e.g. walking, chewing). Eight legged scorpion robot Hadrurus arizonensis

  7. CPG Based Locomotion Control (II)

  8. Adaptive control based on proprioceptive data Adaptive Proprioceptive Control (I) • Key idea and innovation for compliant legs: • No fixed motion pattern for different types of terrain • Adjustment of CPG internal control loop • Use of „adaptive spring“, based on proprioceptive data (energy distribution for each leg)

  9. Adaptive Proprioceptive Control (II) • Online adaptation of internal position controller by adjusting the proportional factor in correlation with the current discrepancy

  10. Fig. 1: Front Left Fig. 2: Front Right Fig. 3: Rear Left Fig. 4: Rear Right Results (I): Phase Sync Without Adaptive Control

  11. Fig. 1: Front Left Fig. 2: Front Right Fig. 3: Rear Left Fig. 4: Rear Right Results (II): Phase Sync With Adaptive Control

  12. Results (III): Demonstration of Mobility

  13. Outlook • Investigation about different gaits in terms of efficiency/speed • Research about adaptive gait transitions • Next prototype (waterproof) already under development • Increase autonomy in terms of navigation under Asguards odometry constraints

  14. Questions?/Comments? Thank you for your attention