Topic
Motion planning
About: Motion planning is a research topic. Over the lifetime, 32846 publications have been published within this topic receiving 553548 citations.
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TL;DR: This survey describes the families of methods for sampling-based planning with constraints and places them on a spectrum delineated by their complexity and focuses on the representation of constraints and sampling- based planners that incorporate constraints.
Abstract: Robots with many degrees of freedom (eg, humanoid robots and mobile manipulators) have increasingly been employed to accomplish realistic tasks in domains such as disaster relief, spacecraft logi
126 citations
01 Sep 2017
TL;DR: FROST is presented, an open-source MATLAB toolkit for modeling, trajectory optimization and simulation of hybrid dynamical systems with a particular focus in dynamic locomotion, which has been successfully used to synthesize dynamic walking in multiple bipedal robots.
Abstract: This paper presents FROST, an open-source MATLAB toolkit for modeling, trajectory optimization and simulation of hybrid dynamical systems with a particular focus in dynamic locomotion. The design objective of FROST is to provide a unified software environment for developing model-based control and motion planning algorithms for robotic systems whose dynamics is hybrid in nature. In particular, FROST uses directed graphs to describe the underlying discrete structure of hybrid system models, which renders it capable of representing a wide variety of robotic systems. Equipped with a custom symbolic math toolbox in MATLAB using Wolfram Mathematica, one can rapidly prototype the mathematical model of robot kinematics and dynamics and generate optimized code of symbolic expressions to boost the speed of optimization and simulation in FROST. In favor of agile and dynamic behaviors, we utilize virtual constraint based motion planning and feedback controllers for robotic systems to exploit the full-order dynamics of the model. Moreover, FROST provides a fast and tractable framework for planning optimal trajectories of hybrid dynamical systems using advanced direct collocation algorithms. FROST has been successfully used to synthesize dynamic walking in multiple bipedal robots. Case studies of such applications are considered in this paper, wherein different types of walking gaits are generated for two specific humanoid robots and validated in simulation.
126 citations
TL;DR: The method builds on the concept of reciprocal velocity obstacles and extends it to respect the kinodynamic constraints of the robot and account for a grid-based map representation of the environment and solve an optimization in the space of control velocities with additional constraints.
Abstract: In this paper, we present a method, namely $\epsilon$ CCA, for collision avoidance in dynamic environments among interacting agents, such as other robots or humans. Given a preferred motion by a global planner or driver, the method computes a collision-free local motion for a short time horizon, which respects the actuator constraints and allows for smooth and safe control. The method builds on the concept of reciprocal velocity obstacles and extends it to respect the kinodynamic constraints of the robot and account for a grid-based map representation of the environment. The method is best suited for large multirobot settings, including heterogeneous teams of robots, in which computational complexity is of paramount importance and the robots interact with one another. In particular, we consider a set of motion primitives for the robot and solve an optimization in the space of control velocities with additional constraints. Additionally, we propose a cooperative approach to compute safe velocity partitions in the distributed case. We describe several instances of the method for distributed and centralized operation and formulated both as convex and nonconvex optimizations. We compare the different variants and describe the benefits and tradeoffs both theoretically and in extensive experiments with various robotic platforms: robotic wheelchairs, robotic boats, humanoid robots, small unicycle robots, and simulated cars.
126 citations
TL;DR: The obstacle-negotiation problem is solved by using a combination of a robust path-following behavior and a reactive obstacle-avoidance behavior that move the robot around a given obstacle at a predefined safety distance.
126 citations
01 Jan 2009
TL;DR: The observation that the computations of the robot motions and the obstacle movements can be decouple is made, and a probabilistically complete algorithm is presented, which maintains an explicit representation of a robot’s configuration space.
Abstract: In this paper we study the problem of path planning among movable obstacles, in which a robot is allowed to move the obstacles if they block the robot’s way from a start to a goal position. We make the observation that we can decouple the computations of the robot motions and the obstacle movements, and present a probabilistically complete algorithm, something which to date has not been achieved for this problem. Our algorithm maintains an explicit representation of the robot’s configuration space. We present an efficient implementation for the case of planar, axis-aligned environments and report experimental results on challenging scenarios.
126 citations