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We introduce Pinocchio, an open-source software framework that implements rigid body dynamics algorithms and their analytical derivatives. Pinocchio does not only include standard algorithms employed in robotics (e.g., forward and inverse dynamics) but provides additional features essential for the control, the planning and the simulation of robots. In this paper, we describe these features and detail the programming patterns and design which make Pinocchio efficient. We evaluate the performances against RBDL, another framework with broad dissemination inside the robotics community. We also demonstrate how the source code generation embedded in Pinocchio outperforms other approaches of state of the art.

This paper addresses the problem of planning paths for an elastic object from an initial to a final configuration in a static environment. It is assumed that the object is manipulated by two actuators and that it does not touch the obstacles in its environment at any time. The object may need to deform to achieve a collision-free path from the initial to the final configuration. Any required deformations are automatically computed by the planner according to the principles of elasticity theory from mechanics. The problem considered in this paper differs significantly from that of planning for a rigid or an articulated object. In the first part of the paper, the authors point out these differences and highlight the reasons that make planning for elastic objects an extremely difficult task. The authors then present a randomized algorithm for computing collision-free paths for elastic objects under the above-mentioned restrictions of manipulation. The paper includes a number of experimental results. The work is motivated by the need to consider the physical properties of objects while planning and has applications in industrial problems, in maintainability studies, in virtual reality environments, and in medical surgical settings.

Fig. 10. Distance (7) versus initial orientation (left) of robot R from the segment P P (right). [Fig. 10 (right)]; as expected, while the robot turns, the distance is smooth almost everywhere [Fig. 10 (left)]. Values for the robot and the segment are R1 : l1 = 0:28 1 = =6 R 2 : l 2 = 0:2 2 = 3=4 R 3 : l 3 = 0:2 3 = 5=4 R 4 : l 4 = 0:28 4 = 11=6 P1 : (00:3; 0:4) P 2 : (0:3; 0:4): VII. CONCLUSIONIn this paper, we presented an analytical method to compute the nonholonomic distance of a polygonal RS car from a polygonal obstacle. By extending the original RS work, we computed the shortest distance to a manifold (the C-obstacle), rather than to a point. In particular, we were able to reduce this problem to that of finding the solution of a set of algebraic equations by using geometric and optimal control arguments, which also provided deeper understanding of the underlying structure of the shortest paths. Moreover, the distance d() being a piecewise smooth function of the robot state , it is easy to compute analytically the gradient 0 ! r d() almost everywhere; thus, it is possible to build an artificial potential field with d(). The computation of a candidate optimal path is performed in constant time. For a robot and an environment with m and n vertices, respectively, the complexity is O(3 3 m 3 n 3 26), where 3 accounts for the three subproblems that must be solved to compute the distance, and 26 accounts for the number of candidate paths whose length will determine the distance value. REFERENCES[1] J. Latombe, Robot Motion Planning. Boston, MA: Kluwer, 1991.[2] J.-P. Laumond and P. Souères, "Metric induced by the shortest paths for a car-like mobile robot," in Proc. Int. Conf. Intell. Robots Syst., 1993, pp. 1299-1303 [3] L. Dubins, "On curves of minimal length with a constraint on average curvature and with prescribed initial and terminal positions and tangents," Amer.Abstract-This paper addresses the scan matching problem for mobile robot displacement estimation. The contribution is a new metric distance and all the tools necessary to be used within the iterative closest point framework. The metric distance is defined in the configuration space of the sensor, and takes into account both translation and rotation error of the sensor. The new scan matching technique ameliorates previous methods in terms of robustness, precision, convergence, and computational load. Furthermore, it has been extensively tested to validate and compare this technique with existing methods.Index Terms-Mobile robots, scan matching, sensor displacement estimation.

Abstract-The upcoming generation of humanoid robots will have to be equipped with state-of-the-art technical features along with high industrial quality, but they should also offer the prospect of effective physical human interaction. In this paper we introduce a new humanoid robot capable of interacting with a human environment and targeting industrial applications. Limitations are outlined and used together with the feedback from the DARPA Robotics Challenge, and other teams leading the field in creating new humanoid robots. The resulting robot is able to handle weights of 6 kg with an out-stretched arm, and has powerful motors to carry out fast movements. Its kinematics have been specially designed for screwing and drilling motions. In order to make interaction with human operators possible, this robot is equipped with torque sensors to measure joint effort and high resolution encoders to measure both motor and joint positions.The humanoid robotics field has reached a stage where robustness and repeatability is the next watershed. We believe that this robot has the potential to become a powerful tool for the research community to successfully navigate this turning point, as the humanoid robot HRP-2 was in its own time.

Abstract-This paper presents a novel and generic approach of path optimization for nonholonomic systems. The approach is applied to the problem of reactive navigation for nonholonomic mobile robots in highly cluttered environments. A collision-free initial path being given for a robot, obstacles detected while following this path can make it in collision. The current path is iteratively deformed in order to ge away from obtacles and satisfy the nonholonomic constraints. The core idea of the approach is to perturb the input functions of the system along the current path in order to modify this path, making an optimization criterion decrease.

Abstract-In this paper, we propose a novel and coherent framework for fast footstep planning for legged robots on a flat ground with 3D obstacle avoidance. We use swept volume approximations computed offline in order to considerably reduce the time spent in collision checking during the online planning phase, in which an RRT variant is used to find collision-free sequences of half-steps (produced by a specific walking pattern generator). Then, an original homotopy is used to smooth the sequences into natural motions avoiding gently the obstacles. The results are experimentally validated on the robot HRP-2.