Florent Lamiraux

Humanoid flexibility deformation can be efficiently estimated using only inertial measurement units and contact information

Most robots are today controlled as being entirely rigid. But often, as for HRP-2 robot, there are flexible parts, intended for example to absorb impacts. The deformation of this flexibility changes the configuration of the robot, particularly in orientation. Nevertheless, robots have usually inertial sensors (IMUs) to reconstruct their orientation based on gravity and inertial effects. Moreover, humanoids have usually to ensure a firm contact with the ground, which provides reliable information on the surrounding environment. We show in this study, how important it is to take into account these information to improve IMU-based position/orientation reconstruction. We use an extended Kaiman filter to rebuild the deformation, making the fusion between IMU and contact information, and without making any assumption on the dynamics of the flexibility. We show how, with this simple setting, we are able to compensate for perturbations and to stabilize the end-effectors position/orientation in the world reference frame.

Approximation of feasibility tests for reactive walk on HRP-2

We present here an original approach to test the feasibility of footsteps for a given walking pattern generator. It is based on a new approximation algorithm intended to cope with this specific problem. The result obtained is used on the robot HRP-2, and enables it to guess a step feasibility 40,000 times faster (in 9µs) than with the normal verification process. As a consequence some advance is made towards fast online motion (re)planning based on a continuous set of possible steps.

HPP: A new software for constrained motion planning

We present HPP, a software designed for complex classes of motion planning problems, such as navigation among movable objects, manipulation, contact-rich multiped locomotion, or elastic rods in cluttered environments. HPP is an open-source answer to the lack of a standard framework for these important issues for robotics and graphics communities.

A framework for manipulation and locomotion with realtime footstep replanning

This paper focuses on realization of tasks with locomotion on humanoid robots. Locomotion and whole body movement are resolved as one unique problem. The same planner and controller are used for both stages of the movement. Final posture and footprint placements are found by resolving an optimization problem on the robot augmented by its footprints. Footstep replanning is done in realtime to correct perception and execution errors. The framework is demonstrated with the HRP-2 robot in a number of different scenarios.

Estimation of contact forces and floating base kinematics of a humanoid robot using only Inertial Measurement Units

A humanoid robot is underactuated and only relies on contacts with environment to move in the space. The ability to measure contact forces and torques enables then to predict the robot dynamics including balance. In classical cases, a humanoid robot is considered as a multi-body system with rigid limbs and joints and interactions with the environment are modeled as stiff contacts. Forces and torques at contacts are generally estimated with sensors which are expensive and sensitive to calibration errors. However, a robot is not perfectly rigid and contacts may have flexibilities. Therefore, external forces create geometric deformations of the body or its environment. These deformations may modify the robot dynamics and produce unwanted and unbalanced motions. Nonetheless, if we have a model of contact stiffness and are able to reconstruct reliably the geometric deformation, we can reconstruct forces and torques at contact. This study aims at estimating contact forces and torques and to observe the body kinematics of the robot with only an Inertial Measurements Unit (IMU). We show that we are able to reconstruct efficiently the position of the Center of Pressure (CoP) of the robot with only the IMU and proprioceptive data from the robot.

Fusion of force-torque sensors, inertial measurements units and proprioception for a humanoid kinematics-dynamics observation

We present a scheme where the measurements obtained through inertial measurement units (IMU), contact-force sensors and proprioception (joint encoders) are merged in order to observe humanoid unactuated floating-base dynamics. The sensor data fusion is implemented using an Extended Kalman Filter. The prediction part is constituted by viscoelastic contacts assumption and a model expressing at the origin the full body dynamics. The correction is achieved using embedded IMU and force sensor. Simulation and experimentation on HRP-2 robot show a state observation with improves inter-sensor consistency but also increased reconstruction accuracy.

Motion planning and irreducible trajectories

We introduce a novel notion for lowering the dimensionality of motion planning problems: Irreducibility. Irreducibility of a configuration space trajectory τ means: We cannot find another configuration space trajectory τ, such that the swept volume of τ is included in the swept volume of τ. The main contribution of our work is twofold: First, we show that motion planning in the space of irreducible trajectories is complete. Second, we show that we can construct reducible subspaces by reasoning about the inherent hierarchical structure of open kinematic chains. Using those theoretical results, we proceed by analytically defining a 7-dimensional irreducible configuration subspace for the humanoid robot HRP-2 under some assumptions. To show its practical importance, we solve a high-dimensional pin-hole problem for HRP-2 from the scratch.

Manipulation planning: Addressing the crossed foliation issue

This paper deals with manipulation planning. First, we propose a new tool called the constraint graph to describe the various motion constraints relative to a manipulation planning problem. Then, we describe a problem arising for some manipulation planning problems called the crossed foliation issue. We propose a extension of RRT algorithm that explores the leaves of the foliations generated by motion constraints and that solves the crossed foliation problem. Finally, we show a wide variety of problem that our approach can solve.

Stabilization of a compliant humanoid robot using only Inertial Measurement Units with a viscoelastic reaction mass pendulum model

To guarantee its balance, a humanoid robot has to respect some contact force constraints. Therefore, traditional controllers generate motions complying with these constraints, but they usually consider the robot as stiff and the joint position perfectly known. However, several robots contain compliant parts in their structure. This flexibility modifies the forces at contacts and endangers balance. However, most solutions to stabilize the robot rely on force sensors. But several humanoid robots arent equipped with these sensors. This paper has two aims. The first one is to develop a compliance stabilizer using the center of mass position and upper-body orientation through a viscoelastic reaction mass pendulum model. The second objective is to show the performances of such a stabilizer when relying only on an IMU-based state observer. Experimental results on HRP-2 robot show that the stabilization successfully rejects perturbations with high gains using only these IMU signals. Moreover, the actuation of the upper-body orientation provides redundancy, robustness and finally improved performances to the stabilizer.