10 results
(View BibTeX file of all listed publications)
2020
Towards Hybrid Active and Passive Compliant Mechanisms in Legged Robots
Milad Shafiee Ashtiani, A. A. S., Badri-Sproewitz, A.
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE, October 2020 (poster) Accepted
VP above or below? A new perspective on the story of the virtual point
Drama, Ö., Badri-Spröwitz, A.
Dynamic Walking, May 2020 (poster)
The spring inverted pendulum model with an extended trunk (TSLIP) is widely used to investigate the postural stability in bipedal locomotion [1, 2]. The challenge of the model is to define a hip torque that generates feasible gait patterns while stabilizing the floating trunk. The virtual point (VP) method is proposed as a simplified solution, where the hip torque is coupled to the passive compliant leg force via a virtual point. This geometric coupling is based on the assumption that the instantaneous ground reaction forces of the stance phase (GRF) intersect at a single virtual point.
Viscous Damping in Legged Locomotion
Mo, A., Izzi, F., Haeufle, D. F. B., Badri-Spröwitz, A.
Dynamic Walking, May 2020 (poster)
Damping likely plays an essential role in legged animal locomotion, but remains an insufficiently understood mechanism. Intrinsic damping muscle forces can potentially add to the joint torque output during unexpected impacts, stabilise movements, convert the system’s energy, and reject unexpected perturbations.
How Quadrupeds Benefit from Lower Leg Passive Elasticity
Ruppert, F., Badri-Spröwitz, A.
Dynamic Walking, May 2020 (poster)
Recently developed and fully actuated, legged robots start showing exciting locomotion capabilities, but rely heavily on high-power actuators, high-frequency sensors, and complex locomotion controllers. The engineering solutions implemented in these legged robots are much different compared to animals. Vertebrate animals share magnitudes slower neurocontrol signal velocities [1] compared to their robot counterparts. Also, animals feature a plethora of cascaded and underactuated passive elastic structures [2].
Potential for elastic soft tissue deformation and mechanosensory function within the lumbosacral spinal canal of birds
Kamska, V., Daley, M., Badri-Spröwitz, A.
Society for Integrative and Comparative Biology Annual Meeting (SICB Annual Meeting 2020), January 2020 (poster)
2019
Das Tier als Modell für Roboter, und Roboter als Modell für Tiere
Badri-Spröwitz, A.
In pages: 167-175, Springer, 2019 (incollection)
2018
Untersuchung und Charakterisierung von Teilelementen der Modifikation im Lumbosacralbereich von Vögeln
Hochschule Harz, 2018 (thesis)
2013
Motor Control Adaptation to Changes in Robot Body Dynamics for a Compliant Quadruped Robot
Pouya, S., Eckert, P., Spröwitz, A., Moc̈kel, R., Ijspeert, A. J.
In Biomimetic and Biohybrid Systems, 8064, pages: 434-437, Lecture Notes in Computer Science, Springer, Heidelberg, 2013 (incollection)
One of the major deficiencies of current robots in comparison to living beings is the ability to adapt to new conditions either resulting from environmental changes or their own dynamics. In this work we focus on situations where the robot experiences involuntary changes in its body particularly in its limbs’ inertia. Inspired from its biological counterparts we are interested in enabling the robot to adapt its motor control to the new system dynamics. To reach this goal, we propose two different control strategies and compare their performance when handling these modifications. Our results show substantial improvements in adaptivity to body changes when the robot is aware of its new dynamics and can exploit this knowledge in synthesising new motor control.
2010
Distributed Online Learning of Central Pattern Generators in Modular Robots
Christensen, D. J., Spröwitz, A., Ijspeert, A. J.
In From Animals to Animats 11, 6226, pages: 402-412, Lecture Notes in Computer Science, Springer, Berlin, 2010, author: Doncieux, Stéphan (incollection)
In this paper we study distributed online learning of locomotion gaits for modular robots. The learning is based on a stochastic ap- proximation method, SPSA, which optimizes the parameters of coupled oscillators used to generate periodic actuation patterns. The strategy is implemented in a distributed fashion, based on a globally shared reward signal, but otherwise utilizing local communication only. In a physics-based simulation of modular Roombots robots we experiment with online learn- ing of gaits and study the effects of: module failures, different robot morphologies, and rough terrains. The experiments demonstrate fast online learning, typically 5-30 min. for convergence to high performing gaits (≈ 30 cm/sec), despite high numbers of open parameters (45-54). We conclude that the proposed approach is efficient, effective and a promising candidate for online learning on many other robotic platforms.