465 research outputs found

    On the completeness of ensembles of motion planners for decentralized planning

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    We provide a set of sufficient conditions to establish the completeness of an ensemble of motion planners-that is, a set of loosely-coupled motion planners that produce a unified result. The planners are assumed to divide the total planning problem across some parameter space(s), such as task space, state space, action space, or time. Robotic applications have employed ensembles of planners for decades, although the concept has not been formally unified or analyzed until now. We focus on applications in multi-robot navigation and collision avoidance. We show that individual resolutionor probabilistically-complete planners that meet certain communication criteria constitute a (respectively, resolution- or probabilistically-) complete ensemble of planners. This ensemble of planners, in turn, guarantees that the robots are free of deadlock, livelock, and starvation.Boeing Compan

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

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    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

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    Podeu consultar la versió en castellà a: http://hdl.handle.net/11703/10236

    A New Approach to Time-Optimal Path Parameterization based on Reachability Analysis

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    Time-Optimal Path Parameterization (TOPP) is a well-studied problem in robotics and has a wide range of applications. There are two main families of methods to address TOPP: Numerical Integration (NI) and Convex Optimization (CO). NI-based methods are fast but difficult to implement and suffer from robustness issues, while CO-based approaches are more robust but at the same time significantly slower. Here we propose a new approach to TOPP based on Reachability Analysis (RA). The key insight is to recursively compute reachable and controllable sets at discretized positions on the path by solving small Linear Programs (LPs). The resulting algorithm is faster than NI-based methods and as robust as CO-based ones (100% success rate), as confirmed by extensive numerical evaluations. Moreover, the proposed approach offers unique additional benefits: Admissible Velocity Propagation and robustness to parametric uncertainty can be derived from it in a simple and natural way.Comment: 15 pages, 9 figure

    Bearing-only formation control with auxiliary distance measurements, leaders, and collision avoidance

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    We address the controller synthesis problem for distributed formation control. Our solution requires only relative bearing measurements (as opposed to full translations), and is based on the exact gradient of a Lyapunov function with only global minimizers (independently from the formation topology). These properties allow a simple proof of global asymptotic convergence, and extensions for including distance measurements, leaders and collision avoidance. We validate our approach through simulations and comparison with other stateof-the-art algorithms.ARL grant W911NF-08-2-0004, ARO grant W911NF-13-1-0350, ONR grants N00014-07-1-0829, N00014-14-1-0510, N00014-15-1-2115, NSF grant IIS-1426840, CNS-1521617 and United Technologies
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