Material Recognition CNNs and Hierarchical Planning for Biped Robot Locomotion on Slippery Terrain

In this paper we tackle the problem of visually predicting surface friction for environments with diverse surfaces, and integrating this knowledge into biped robot locomotion planning. The problem is essential for autonomous robot locomotion since diverse surfaces with varying friction abound in the real world, from wood to ceramic tiles, grass or ice, which may cause difficulties or huge energy costs for robot locomotion if not considered. We propose to estimate friction and its uncertainty from visual estimation of material classes using convolutional neural networks, together with probability distribution functions of friction associated with each material. We then robustly integrate the friction predictions into a hierarchical (footstep and full-body) planning method using chance constraints, and optimize the same trajectory costs at both levels of the planning method for consistency. Our solution achieves fully autonomous perception and locomotion on slippery terrain, which considers not only friction and its uncertainty, but also collision, stability and trajectory cost. We show promising friction prediction results in real pictures of outdoor scenarios, and planning experiments on a real robot facing surfaces with different friction

Multi-contact Walking Pattern Generation based on Model Preview Control of 3D COM Accelerations

We present a multi-contact walking pattern generator based on preview-control of the 3D acceleration of the center of mass (COM). A key point in the design of our algorithm is the calculation of contact-stability constraints. Thanks to a mathematical observation on the algebraic nature of the frictional wrench cone, we show that the 3D volume of feasible COM accelerations is a always a downward-pointing cone. We reduce its computation to a convex hull of (dual) 2D points, for which optimal O(n log n) algorithms are readily available. This reformulation brings a significant speedup compared to previous methods, which allows us to compute time-varying contact-stability criteria fast enough for the control loop. Next, we propose a conservative trajectory-wide contact-stability criterion, which can be derived from COM-acceleration volumes at marginal cost and directly applied in a model-predictive controller. We finally implement this pipeline and exemplify it with the HRP-4 humanoid model in multi-contact dynamically walking scenarios

Generating Humanoid Multi-Contact through Feasibility Visualization

We present a feasibility-driven teleoperation framework designed to generate humanoid multi-contact maneuvers for use in unstructured environments. Our framework is designed for motions with arbitrary contact modes and postures. The operator configures a pre-execution preview robot through contact points and kinematic tasks. A fast estimation of the preview robot's quasi-static feasibility is performed by checking contact stability and collisions along an interpolated trajectory. A visualization of Center of Mass (CoM) stability margin, based on friction and actuation constraints, is displayed and can be previewed if the operator chooses to add or remove contacts. Contact points can be placed anywhere on a mesh approximation of the robot surface, enabling motions with knee or forearm contacts. We demonstrate our approach in simulation and hardware on a NASA Valkyrie humanoid, focusing on multi-contact trajectories which are challenging to generate autonomously or through alternative teleoperation approaches

ZMP support areas for multi-contact mobility under frictional constraints

We propose a method for checking and enforcing multi-contact stability based on the Zero-tilting Moment Point (ZMP). The key to our development is the generalization of ZMP support areas to take into account (a) frictional constraints and (b) multiple non-coplanar contacts. We introduce and investigate two kinds of ZMP support areas. First, we characterize and provide a fast geometric construction for the support area generated by valid contact forces, with no other constraint on the robot motion. We call this set the full support area. Next, we consider the control of humanoid robots using the Linear Pendulum Mode (LPM). We observe that the constraints stemming from the LPM induce a shrinking of the support area, even for walking on horizontal floors. We propose an algorithm to compute the new area, which we call pendular support area. We show that, in the LPM, having the ZMP in the pendular support area is a necessary and sufficient condition for contact stability. Based on these developments, we implement a whole-body controller and generate feasible multi-contact motions where an HRP-4 humanoid locomotes in challenging multi-contact scenarios.Comment: 14 pages, 10 figure

Multi-contact Planning on Humans for Physical Assistance by Humanoid

International audienceFor robots to interact with humans in close proximity safely and efficiently, a specialized method to compute whole-body robot posture and plan contact locations is required. In our work, a humanoid robot is used as a caregiver that is performing a physical assistance task. We propose a method for formulating and initializing a non-linear optimization posture generation problem from an intuitive description of the assistance task and the result of a human point cloud processing. The proposed method allows to plan whole-body posture and contact locations on a task-specific surface of a human body, under robot equilibrium, friction cone, torque/joint limits, collision avoidance, and assistance task inherent constraints. The proposed framework can uniformly handle any arbitrary surface generated from point clouds, for autonomously planing the contact locations and interaction forces on potentially moving, movable, and deformable surfaces, which occur in direct physical human-robot interaction. We conclude the paper with examples of posture generation for physical human-robot interaction scenarios

Admissible Velocity Propagation : Beyond Quasi-Static Path Planning for High-Dimensional Robots

Path-velocity decomposition is an intuitive yet powerful approach to address the complexity of kinodynamic motion planning. The difficult trajectory planning problem is solved in two separate, simpler, steps: first, find a path in the configuration space that satisfies the geometric constraints (path planning), and second, find a time-parameterization of that path satisfying the kinodynamic constraints. A fundamental requirement is that the path found in the first step should be time-parameterizable. Most existing works fulfill this requirement by enforcing quasi-static constraints in the path planning step, resulting in an important loss in completeness. We propose a method that enables path-velocity decomposition to discover truly dynamic motions, i.e. motions that are not quasi-statically executable. At the heart of the proposed method is a new algorithm -- Admissible Velocity Propagation -- which, given a path and an interval of reachable velocities at the beginning of that path, computes exactly and efficiently the interval of all the velocities the system can reach after traversing the path while respecting the system kinodynamic constraints. Combining this algorithm with usual sampling-based planners then gives rise to a family of new trajectory planners that can appropriately handle kinodynamic constraints while retaining the advantages associated with path-velocity decomposition. We demonstrate the efficiency of the proposed method on some difficult kinodynamic planning problems, where, in particular, quasi-static methods are guaranteed to fail.Comment: 43 pages, 14 figure

Model preview control in multi-contact motion-application to a humanoid robot

International audienceOur work builds largely on Nagasaka's stabilizer in multi-contact motion [1]. Using a sequence of contact stances from an offline multi-contact planner, we use first a Model Predictive Controller to generate a dynamic trajectory of the center of mass, then a whole-body closed-loop model-based controller to track it at best. Relatively to Nagasaka's work, we allow frame changes of the preferred force, provide a heuristic to compute the timing of the transition from purely geometrical features and investigate the synchronization problem between the reduced-model preview control and the whole-body controller. Using our framework, we generate a wide range of 3D motions, while accounting for predictable external forces, which includes transporting objects. Simulation scenarios are presented and obtained results are analyzed and discussed