We study the effect of soft (i.e. compliant) soles in humanoid walking. Adding compliance at the foot sole is important for shock absorption during touchdown and to better cast the ground roughness. But, subsequent deformation needs to be considered in the attitude stabilization. We propose a sole deformation estimator used in the controller design, to ensure that the desired ZMP for stability requirement is fulfilled. We performed two comparison experiments on the HRP-4 humanoid robot with/without the estimator. Experiments showed how the estimator enhances the ZMP stabilization during walking and prevents the robot from falling down.

We propose a new bounding volume that achieves a tunable strict convexity of a given convex hull. This geometric operator is named sphere-tori-patches bounding volume (STP-BV), which is the acronym for the bounding volume made of patches of spheres and tori. The strict convexity of STP-BV guarantees a unique pair of witness points and at least C1continuity of the distance function resulting from a proximity query with another convex shape. Subsequently, the gradient of the distance function is continuous. This is useful for integrating distance as a constraint in robotic motion planners or controllers using smooth optimization techniques. For the sake of completeness, we compare performance in smooth and nonsmooth optimization with examples of growing complexity when involving distance queries between pairs of convex shapes.

STP-BV is a bounding volume made of patches of spheres and toruses. These patches are assembled so that a convex polyhedral hull is bulged, in a tunable way, into a strictly convex form. Strict convexity ensures at least C1property of the distance function -and hence, its gradient continuity. STP-BV were introduced in our previous work [1], but proximity distance queries were limited to pairs of STP-BV covered objects. In this work we present an alternative to achieve fast proximity distance queries between a STP-BV object and any other convex shape. This is simply made by proposing a support mapping for STP-BV to be used with GJK algorithm [2] and its EPA extension to penetration cases [3]. Implementation and experiments of the proposed method and its performance are demonstrated with potential applications to robotics and computer graphics.

This paper presents a method for sequencing a set of robotic tasks in an optimal way. Tasks description and execution are based on the task-function approach, which enables to build complex whole-body behaviors from local control laws. A naive solution to this problem would be to schedule the execution of the tasks sequentially, avoiding concurrency. This solution does not exploit full robot capabilities such as redundancy and have poor performance in terms of execution time or energy. However, reasoning on concurrent tasks is difficult while accounting for all the physical constraints of the robot. Our contribution is to determine the time-optimal realization of the mission taking into account robotic constraints that may be as complex as collision avoidance. Our approach achieves more than a simple scheduling; its originality lies in maintaining the task approach in the formulated optimization of the task sequencing problem. This theory is exemplified through a complete experiment on the real HRP-2 robot.

This paper proposes a real-time implementation of collision and self-collision avoidance for robots. On the basis of a new proximity distance computation method which ensures having continuous gradient, a new controller in the velocity domain is proposed. The gradient continuity encompasses no jump in the generated command. Included in a stack of tasks architecture, this controller has been implemented on the humanoid platform HRP-2 and experienced in a grasping task while walking and avoiding collisions with the environment and auto-collisions.

A motion control method of lifting a heavy object up to a higher position with humanoid robots is developed. The key issue of lifting motion is how to reduce the load on humanoid arms in which low-power actuators are implemented. The use of singular postures of arms is well-known to avoid actuator saturation of the arms. By combining two different kinds of humanoid motions such as accelerating an object upward and sliding the body into under the object, we propose a method that enables to transit one singular posture of arms to another while lifting the object. Simulation results show the effectiveness of the proposed method for reducing the load on the arms. We realize a motion of lifting a heavy object dynamically with the humanoid robot HRP-2 through experiment.

In multimodal tele-cooperation as considered in this paper two humans in distant locations jointly perform a task requiring multimodal including haptic feedback. One human operator teleoperates a remotely placed humanoid robot which is collocated with the human cooperator. Time delay in the communication channel as destabilizing factor is one of the multiple challenges associated with such a tele-cooperation setup. In this paper we employ a control architecture with force-position exchange accounting for the admittance type of the haptic input device and the telerobot, which both are position-based admittance controlled. Llewellynpsilas stability criteria are employed for the parameter tuning of the virtual impedances in the presence of time delay. The control strategy is successfully validated in an intercontinental tele-cooperation experiment with the humanoid telerobot HRP-2 located in Japan/Tsukuba and a multimodal human-system-interface located in Germany/Munich, see also the corresponding video submission. The proposed setup gives rise to a large number of exciting new research questions to be addressed in the future.

The video shows an intercontinental cooperative telemanipulation task, whereby the operator site is located in Munich, Germany and the teleoperator site in Tsukuba, Japan. The human operator controls a remotely located teleoperator, which performs a task in the remote environment. Hereby the human operator is assisted by another person located at the remote site. The task consists in jointly grasping an object, moving it to a new position and finally releasing it, see Fig. 1.

This paper deals with the motion planning of a polyarticulated robotic system for which support contacts are allowed to occur between any part of the body and any part of the environment. Starting with a description of the environment and of a target, it computes a sequence of postures that allow our system to reach its target. We describe a very generic architecture of this planner, highly modular, as well as a first implementation of it. We then present our results, both simulations and real experiments, for a simple grasping task using the HRP-2 humanoid robot