21 Feb 2017 . Manipulation planning for documented objects (BIBTEX)
Joseph Mirabel
Université Fédérale de Toulouse

Thesis manuscript

Dissertation | Defense slides (without videos ~ 9M) | Defense slides (full ~ 93M)

Abstract

This thesis tackles the manipulation planning for documented objects. The difficulty of the problem is the coupling of a symbolic and a geometrical problem. Classical approaches combine task and motion planning. They are hard to implement and time consuming. This approach is different on three aspects.

The first aspect is a theoretical framework to model admissible motions of the robot and objects. This model uses constraints to link symbolic task and motions achieving such task. A graph of constraint models the manipulation rules. A planning algorithm using this graph is proposed.

The second aspect is the handling of constrained motion. In manipulation planning, an abstract definition of numerical constraint is necessary. A continuity criterion for Newton-Raphson methods is proposed to ensure the continuity of trajectories in sub-manifolds.

The last aspect is object documentation. Some information, easy to define for human beings, greatly speeds up the search. This documentation, specific to each object and end-effector, is used to generate a graph of constraint, easing the problem specification and resolution.

Key words

Manipulation planning, Constrained planning, Continuous trajectory generation, Affordance, Documented objects

Chapters

A summary of each chapter is available (only in French so far).

  1. State of the art
    • Motion planning
    • Task planning
    • Manipulation planning
  2. Constrained motion planning
    • Notations and definitions
    • Continuous path on manifolds
    • Static stability
  3. Manipulation planner
    • Constraint Graph
    • Crossed foliation issue
    • Generalized reduction property
    • Narrow passages
  4. Affordance
    • Documented objects
    • Constraint graph generation
  5. Result
    • Humanoid Path Planner
    • Manipulator arms
    • Humanoid robots