Tech United Eindhoven RoboCup adult size humanoid team description 2012

This document presents the 2012 Tech United Eindhoven adult size humanoid robot team from The Netherlands. The team contributes the adult-size humanoid robot TUlip. Here we present the mechanical design and kinematic structure of the robot. We introduce the walking gait and contribute a controller structure including gravity compensation. Finally, we describe the vision system, self localization and world model, which are used for the attacker and defender strategy in the humanoid robot soccer game

Dutch Robotics 2011 adult-size team description

This document presents the 2011 edition of the team Dutch Robotics from The Netherlands. Our team gathers three Dutch technical universities, namely Delft University of Technology, Eindhoven University of Technology and University of Twente, and the commercial company Philips. We contribute an adult-size humanoid robot TUlip, which is designed based on theory of the limit cycle walking developed in our earlier research. The key of our theory is that stable periodic walking gaits can be achieved even without high-bandwidth robot position control. Our control approach is based on simultaneous position and force control. For accurate force control, we make use of the Series Elastic Actuation. The control software of TUlip is based on the Darmstadt’s RoboFrame, and it runs on a PC104 computer with Linux Xenomai. The vision system consists of two wide-angle cameras, each interfaced with a dedicated Blackfin processor running vision algorithms, and a wireless networking interface

Dutch Robotics 2010 adult-size team description

This document presents the 2010 edition of the team Dutch Robotics from The Netherlands. Our team gathers three Dutch technical universities, namely Delft University of Technology, Eindhoven University of Technology and University of Twente, and the commercial company Philips. We contribute an adult-size humanoid robot TUlip, which is designed based on theory of the limit cycle walking developed in our earlier research. The key of our theory is that stable periodic walking gaits can be achieved even without high-bandwidth robot position control. Our control approach is based on simultaneous position and force control. For accurate force control, we make use of the Series Elastic Actuation. The control software of TUlip is based on the Darmstadt’s RoboFrame, and it runs on a PC104 computer with Linux Xenomai. The vision system consists of two wide-angle cameras, each interfaced with a dedicated Blackfin processor running vision algorithms, and a wireless networking interface

Foot placement indicator for balance of planar bipeds with point feet

When humanoid robots are going to be used in society, they should be capable to maintain the balance. Knowing where to step appears to be crucially important to remain balanced. In this paper we contribute an algorithm for planar bipeds with point feet and an arbitrary number of non-massless links that can compute the foot step location such that bipedal balance is maintained. We call this algorithm the foot placement indicator (FPI). It is based on the foot placement estimator (FPE) and uses conservation of energy throughout the step taking into account the instantaneous impact dynamics at foot strike. A simulation case study on a five-link planar biped shows the effectiveness off the FPI

Gait control by foot placement for humanoid robots

Humanoid robots are used as a research tool to understand bipedal locomotion. When pushed, a humanoid robot must be able to avoid falling and return to a balanced configuration. This is called push recovery and can be achieved using proper foot placement. Depending on the freedom of movement, one or multiple steps are taken to accomplish this goal. It is expected that foot placement can also be used to achieve controlled bipedal walking: gait control. Current foot placement strategies are limited to push recovery or restricted to bipeds with linear dynamics. The purpose of the present study is to achieve gait control by foot placement, for both a 2D biped and a 3D biped model with nonlinear dynamics. For the 2D biped model, the biped velocity at the upright standing configuration is controlled using an extension of the foot placement strategy FPE, which is normally used for 1-step push recovery. Simulations shows that desired reference velocities are obtained for various numbers of steps. For the 3D biped model, gait control is achieved using a new foot placement strategy, called FPP. This strategy is also verified in simulation, showing that gait control can be achieved for multiple reference paths. The findings are beneficial for dynamical analysis, simulation and gait control of bipedal robots