This article presents a software platform tailored for prehensile manipulation planning named humanoid path planner. The platform implements an original way of modeling manipulation planning through a constraint graph that represents the numerical constraints that define the manipulation problem. We propose an extension of the RRT algorithm to manipulation planning that is able to solve a large variety of problems. We provide replicable experimental results via a docker image that readers may download to run the experimental results by themselves.

Self-collision detection and avoidance are essential for reactive control, in particular for dynamics robots equipped with legs or arms. Yet, only few control methods are able to handle such constraints, and it is often necessary to rely on path planning to define a collision-free trajectory that the controller would then track. In this paper, we introduce a combination of two lightweight, conservative and smooth models to generically handle self-collisions in robot control. For pairs of bodies that are far from one another on average (e.g. segments of distinct legs), we rely on a standard forward kinematics approach, using simplified geometries for which we provide analytical derivatives. For bodies that are moving close to one another, we propose to use a data-driven approach, with datasets generated thanks to a standard collision library. We then build a simple torque-based controller that can be implemented on top of any control law to prevent unexpected self-collision. This controller is meant to be implemented as a low-level protection, directly on the robot hardware. We also provide an open-source library to generate ANSI-C code for any robot model, experimented on the real quadruped Solo.

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.

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.