Maneuver-based motion planning for nonlinear systems with symmetries

By Emilio Frazzoli, Munther A. Dahleh, Eric M. Feron. 2005

486 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Control and Systems Engineering

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Citations in the corpus

Transporter Networks: Rearranging the Visual World for Robotic Manipulation (2020, methodology): “We can generalize beyond pick-and-place by considering manipulation with other motion primitives [22] that are also parameterized by two end effector poses.”
Temporal-Logic-Based Reactive Mission and Motion Planning (2009, background): “Maneuver automata [18], which can be seen as a subset of MDLs, are an example for the use of a regular language to solve”
Sampling-Based Robot Motion Planning: A Review (2014, methodology): “trajectory when connecting two configurations, a particularly useful strategy for redundant articulated manipulators [74], or differentially constrained dynamic systems [170].”
Learning to Rearrange Deformable Cables, Fabrics, and Bags with Goal-Conditioned Transporter Networks (2020, background): “The Tpick and Tplace both parameterize a motion primitive [21] that controls the end effector to approach Tpick until contact is detected, activates the end effector to execute a grasp, moves upward to a fixed z-height, approaches Tplace, and lowers the end effector until contact is detected, then r”
A multirange architecture for collision‐free off‐road robot navigation (2009, unknown): “(PiedMonte and Feron, 1999) introduced maneuver-based planning in free environments for aerial vehicles by recording human experts maneuvers, and later developed a maneuver-based automaton (Frazzoli et al., 2005) that can concatenate trajectory primitives with a regular language.”
Survivability: Measuring and ensuring path diversity (2009, background): “For particular systems, the careful construction of effective primitives dramatically improved performance in [2], [3].”
Motion planning with sequential convex optimization and convex collision checking (2014, unknown): “, 2013), and primitive-based motion planning (Frazzoli et al., 2005).”
Time-optimal paths for a Dubins airplane (2007, background): “Frazzoli et al proposed a set of motion primitives, for a six-dimensional aircraft, which contains pieces of optimal trajectories called trim trajectories [18].”
CommonRoad: Composable benchmarks for motion planning on roads (2017, methodology): “uses motion primitives that span a search tree [22].”
Planning algorithms (2006, methodology): “An excellent example of this appears in [365], in which value iteration was used to compute the optimal cost-to-go in the absence of obstacles for an autonomous helicopter using the maneuver automaton model of Figure 14.”
Flying Fast and Low Among Obstacles: Methodology and Experiments (2008, methodology): “Frazzoli et al. (2005) use a concatenation of motion primitives in order to construct valid paths that avoid obstacles and achieve a desired goal pose.”
Nonlinear robust tracking control of a quadrotor UAV on SE(3) (2011, unknown): “This work is also distinct from motion planning results in [28], where an algorithm to solve an open-loop motion 3 T.”
Optimization‐based autonomous racing of 1:43 scale RC cars (2015, background): “The latter reference suggests to use a library of steadystate movements (trims) with parametrizable length, which are generated from a more complex dynamical model, and to connect them by maneuvers which allow the transition from one trim to another, similar to the idea of [18].”
Symbolic planning and control of robot motion [Grand Challenges of Robotics] (2007, background): “In [ 6 ], the following classes of motion primitives have been identified: i) trim primitives and ii) maneuvers.”
Scalable Approach to Uncertainty Quantification and Robust Design of Interconnected Dynamical Systems (2011, unknown): “This general framework developed in [19] is suitable to systems such as UAVs or ground robots if one ignores posedependent external forces, such as varying wind or changing ground friction as function of position.”
Opportunities and challenges with autonomous micro aerial vehicles (2012, background): “These ideas can be formalized to generate three-dimensional motion primitives with symmetries (Frazzoli et al., 2005) and it may be possible to use these primitives with lattice-based motion planning techniques which have been shown to work for simpler kinematic primitives in non-holonomic vehicles ”
Behavioral systems theory in data-driven analysis, signal processing, and control (2021, background): “, trajectories) has often been exploited for motion planning (Frazzoli et al., 2005) or predictive control (Gray et al.”