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Linear And Nonlinear Programming

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Automated Planning: Theory and Practice.

Society is becoming more automated with robots beginning to perform most tasks in factories and starting to help out in home and office environments. One of the most important functions of robots is the ability to manipulate objects in their environment. Because the space of possible robot designs, sensor modalities, and target tasks is huge, researchers end up having to manually create many models, databases, and programs for their specific task, an effort that is repeated whenever the task changes. Given a specification for a robot and a task, the presented framework automatically constructs the necessary databases and programs required for the robot to reliably execute manipulation tasks. It includes contributions in three major components that are critical for manipulation tasks. 
The first is a geometric-based planning system that analyzes all necessary modalities of manipulation planning and offers efficient algorithms to formulate and solve them. This allows identification of the necessary information needed from the task and robot specifications. Using this set of analyses, we build a planning knowledge-base that allows informative geometric reasoning about the structure of the scene and the robot's goals. We show how to efficiently generate and query the information for planners. 
The second is a set of efficient algorithms considering the visibility of objects in cameras when choosing manipulation goals. We show results with several robot platforms using grippers cameras to boost accuracy of the detected objects and to reliably complete the tasks. Furthermore, we use the presented planning and visibility infrastructure to develop a completely automated extrinsic camera calibration method and a method for detecting insufficient calibration data. 
The third is a vision-centric database that can analyze a rigid object's surface for stable and discriminable features to be used in pose extraction programs. Furthermore, we show work towards a new voting-based object pose extraction algorithm that does not rely on 2D/3D feature correspondences and thus reduces the early-commitment problem plaguing the generality of traditional vision-based pose extraction algorithms. 
In order to reinforce our theoric contributions with a solid implementation basis, we discuss the open-source planning environment OpenRAVE, which began and evolved as a result of the work done in this thesis. We present an analysis of its architecture and provide insight for successful robotics software environments.

Automated construction of robotic manipulation programs

Hierarchical least-square optimization is often used in robotics to inverse a direct function when multiple incompatible objectives are involved. Typical examples are inverse kinematics or dynamics. The objectives can be given as equalities to be satisfied e.g. point-to-point task or as areas of satisfaction e.g. the joint range. This paper proposes a complete solution to solve multiple least-square quadratic problems of both equality and inequality constraints ordered into a strict hierarchy. Our method is able to solve a hierarchy of only equalities 10 times faster than the iterative-projection hierarchical solvers and can consider inequalities at any level while running at the typical control frequency on whole-body size problems. This generic solver is used to resolve the redundancy of humanoid robots while generating complex movements in constrained environments.

/pdf/hierarchical-quadratic-programming-5e14hy8pw1.pdf

Hierarchical quadratic programming

Robotics and autonomous systems

https://hal-lirmm.ccsd.cnrs.fr/lirmm-00800829/document

Planning contact points for humanoid robots

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.

/pdf/real-time-self-collision-avoidance-task-on-a-hrp-2-humanoid-2q06njl42q.pdf

Real-time (self)-collision avoidance task on a hrp-2 humanoid robot

This paper presents software that has been devised for the purpose of optimal motions computation for robots. For the time being, this study considered only open-loop and fully actuated structures. Generated motion satisfies a stability criterion while minimizing energy consumption. Motion optimization is solved with the IPOPT optimization package. In order to achieve fast and reliable optimization convergence, an efficient calculation of gradients is presented. Moreover, almost rarely considered in the literature, joint friction, which has a non- negligible effect on the optimized motion, is taken into account. Efficiency of the proposed software is demonstrated through the optimization of a kicking motion for the 30 degrees of freedom humanoid robot HRP-2.

Development of a software for motion optimization of robots - Application to the kick motion of the HRP-2 robot

This paper deals with the motion planning of a poly-articulated 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.

Planning support contact-points for humanoid robots and experiments on HRP-2

This paper describes results obtained in a preliminary investigation of a cooperative task consisting, for a pair of human operators, in moving a handle-shaped object between two predefined locations on a table. Seated, the operators use only upper body with single hand and arms in achieving this task. In a first step, each subject realized the task in a standalone mode. In a second step, pairs of subjects realized a similar task in a cooperative way. We used standalone results as a reference model to be compared with results obtained from cooperative experiments. Obtained results revealed that it is difficult to fit the minimum jerk model as a task motion characterization in both standalone and cooperative modes. However, we found an invariant velocity shape both for standalone and cooperation situations that can be used as a basic model for a robotic implementation. We noticed that the shape of the parabolic trajectory is always higher in cooperative tasks, although the weight of the object used in cooperative mode is exactly twice the one used in a standalone mode.

/pdf/human-motion-in-cooperative-tasks-moving-object-case-study-3wsmsrx1sj.pdf

Sylvain Miossec

Papers

Planning contact points for humanoid robots

Real-time (self)-collision avoidance task on a hrp-2 humanoid robot

Development of a software for motion optimization of robots - Application to the kick motion of the HRP-2 robot

Planning support contact-points for humanoid robots and experiments on HRP-2

Human motion in cooperative tasks: Moving object case study