ICS, CNE, HCR Research Seminar on October 31, 2018


ICS, CNE, HCR Research Seminar with presentations by:

- Julio Rogelio Guadarrama Olvera, Chair for Cognitive Systems: "Enhancing Biped Locomotion on Unknown Terrain Using Tactile Feedback

Abstract: Human bipedal balance during standing and walking depends on several receptors including the cutaneous receptors in the glabrous skin of the foot sole. It has been shown in human-involved studies that the different areas of the sole have distinct sensitivities and serve a different purpose in both walking and standing. In humanoid robotics, the feedback to keep balance is mainly achieved using force-torque sensors mounted at the robot’s ankles. Although these sensors can accurately estimate the center of pressure of a foothold, they cannot provide information about the pressure shape of the footprint and therefore can miss ill terrain conditions during locomotion. In this paper, we present a biologically inspired sole skin sensor based on the robot skin developed at our lab. The robot skin can enhance and complement the ankle force-torque sensors used in balancing and walking controllers by providing additional information that a force-torque sensor cannot produce. This additional information can be used to reconstruct the supporting polygon and the pressure footprint online. We present a case study where a force-torque sensor fails to detect the terrain conditions while the skin succeeds and the information is used to re-plan the footstep position.

Dennis Ossadnik, Department of Electrical Engineering at TUM: "Adaptive Friction Compensation for Humanoid Robots without Joint-Torque Sensor"

Abstract: This paper presents a novel approach for friction compensation on humanoid robots originally designed for po- sition control in order to enable torque-based control methods on such systems. Due to their design, this kind of robots lacks joint-torque sensors and is equipped with high-reduction gearboxes. Nevertheless, we can still apply torque commands using torque estimation from motor currents. Moreover, the high gear reduction ratio produces high dynamic friction which significantly affects the robots drives and must be taken into account. Considering the LuGre friction model, an adaptive friction compensator based on a second-order sliding mode is developed and illustrated on a humanoid robot. The proposed method only relies on IMU data as well as joint position and velocity measurements from the joint encoders and is applied to the 12 DoFs of the robot’s legs for CoM motion. The proposed control approach does not require the FT sensors mounted on the ankles.

31. October 2018, 16:30, ICS Karlstraße 45, 6. Floor, room 6009

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