Technical session talks from ICRA 2012
TechTalks from event: Technical session talks from ICRA 2012
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Stable Dynamic Walking of a Quadruped "Kotetsu" Using Phase Modulations Based on Leg Loading/Unloading against a Lateral PerturbationWe intend to show the basis of a general legged locomotion controller with the ability to integrate both posture and rhythmic motion controls. We respectively used leg loading and unloading for the phase transitions from swingto- stance and stance-to-swing, and showed the following in our previous 3D model simulation study: (a) as a result of the phase modulations based on leg loading/unloading, rhythmic motion of each leg was achieved and leg coordination (resulting in a gait) emerged, even without explicit coordination among the leg controllers, allowing to realize dynamic walking in the low- to medium-speed range (b) but an additional ascending coordination mechanism between ipsilateral leg controllers was necessary to improve the stability. In this paper, we report on experimental results using â€œKotetsuâ€ under a lateral perturbation while walking and compare them with the results of our previous simulations.
Dynamic Torque Control of a Hydraulic Quadruped RobotLegged robots have the potential to serve as versatile and useful autonomous robotic platforms for use in unstructured environments such as disaster sites. They need to be both capable of fast dynamic locomotion and precise movements. However, there is a lack of platforms with suitable mechanical properties and adequate controllers to advance the research in this direction. In this paper we are presenting results on the novel research platform HyQ, a torque controlled hydraulic quadruped robot. We identify the requirements for versatile robotic legged locomotion and show that HyQ is fulfilling most of these specifications. We show that HyQ is able to do both static and dynamic movements and is able to cope with the mechanical requirements of dynamic movements and locomotion, such as jumping and trotting. The required control, both on hydraulic level (force/torque control) and whole body level (rigid model based control) is discussed.
Kinematic Control and Posture Optimization of a Redundantly Actuated Quadruped RobotAlthough legged locomotion for robots has been studied for many years, the research of autonomous wheel- legged robotics is much more recent. Robots of this type, also described as hybrid, can take advantage of the energy efficiency of wheeled locomotion while adapting to more difficult terrain with legged locomotion when necessary. The Micro Hydraulic Toolkit (MHT), developed by engineers at Defence R&D Canada â€“ Suffield, is a good example of such a robot. Investigation into control and optimization techniques for MHT leads to a better understanding of hybrid vehicle control for terrestrial exploration and reconnaissance. Control of hybrid robots has been studied by several researchers during the last decade. The methodology applied in this work uses an inverse kinematics algorithm developed previously for a hybrid robot Hylos, and implements an optimization technique to minimize torques occurring at crucial actuators. As well, some added functionality is incorporated into the control method to implement stepping maneuvers. This paper will present the results obtained via co-simulation using Matlabâ€™s Simulink and a high-fidelity model of MHT in LMS Virtual Lab.
Optimally Scaled Hip-Force Planning: A Control Approach for Quadrupedal RunningThis paper presents Optimally Scaled Hip-Force Planning (OSHP), a novel approach to controlling the body dynamics of running robots. Controllers based on OSHP form the high-level component of a hierarchical control scheme in which they direct lower level controllers, each responsible for coordinating the motion of a single leg. An OSHP controller takes in the state of the runner at the apex of its primary aerial phase and returns desired profiles for the vertical and horizontal forces to be exerted at each hip during the subsequent stride. The hip force profiles returned by OSHP are scaled variants of nominal force profiles based on biological ground reaction force data. The OSHP controller determines the scaling parameters for these profiles through constrained nonlinear optimization on an approximate model of the runner's body dynamics. Evaluation of an OSHP controller for a quadruped model in simulation shows that even with very simple leg controllers, the OSHP controller can accelerate the runner from rest to steady-state running without a pre-defined footfall sequence.
Enforced Symmetry of the Stance Phase for the Spring-Loaded Inverted PendulumThe Spring-Loaded Inverted Pendulum (SLIP) is considered the simplest model to effectively describe bouncing gaits (such as running and hopping) for many legged animals and robots. For this reason, it is has often been used as a model for robot design. A key challenge in using this model, however, is the lack of a closed-form solution for the equations of motion that define the stance phase of its dynamics. This results in the impossibility of analytically predicting its trajectory. Consequently, developing a practical control strategy to operate on the model is computationally intensive, because accurately predicting the step-to-step dynamics is still an unsolved problem. By adding an actuator in series with the spring, we can develop a control law for actuator displacement which enforces a desired trajectory during stance. In particular, for our specific chosen control law, we can compute an analytical solution for the stance phase trajectory. Furthermore, we give examples of higher level control strategies for foothold placement and for keeping the forward velocity or the apex height constant on rough terrain that employ our low-level control laws, and we illustrate through simulations the performance typical of our strategy.
A Behavior Based Locomotion Controller with Learning for Disturbance Compensation in Bipedal RobotsA novel behavior based locomotion controller (BBLC) capable of adapting to unknown disturbances is presented. The proposed controller implements a behavior based control architecture by subdividing the walking control into several task-space controllers such as swing leg control and center of gravity (COG) position control. For each task-space controller, a number of behaviors, which plan the reference task-space trajectories, are designed based on existing stabilizing controllers or strategies inspired by human walking biomechanics. A Q-learning algorithm is used to classify which behavior combinations can compensate for specific disturbances. The controller is implemented on a planar biped simulation with push type disturbances applied on flat and sloped terrain. The results show that stabilization strategies, capable of compensating for these disturbances emerge from the combination of different task level behaviors, without a priori knowledge of the nature of the disturbances.