Technical session talks from ICRA 2012
TechTalks from event: Technical session talks from ICRA 2012
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Path Planning and Navigation
Reliable Indoor Navigation with an Unreliable Robot: Allowing Temporary Uncertainty for Maximum MobilityIn this work we consider a navigation problem for a very simple robot equipped with only a map, compass, and contact sensor. Our prior work on this problem uses a graph to navigate between the convex vertices of an environment. In this paper, we extend this graph with the addition of a new node type and four new edge types. The new node type allows for more uncertainty in robot position. The presence of one of these new edge types guarantees reliable transitions between these nodes. This enhanced graph enables the algorithm to navigate environment features not solvable by our previous algorithm, including T-junctions and long halls. We also present a heuristic to accelerate the planning process by prioritizing the promising edge tests to perform. Our heuristic effectively focuses the search and qualitative data show that it computes plans with much less computational effort than a naive approach. We describe a simulated implementation of the algorithm that finds paths not previously possible, and a physical implementation that demonstrates the feasibility of executing those plans in practice.
Path Planning in Time Dependent Flow Fields Using Level Set MethodsWe develop and illustrate an efficient but rigorous methodology that predicts the time-optimal paths of ocean vehicles in continuous dynamic flows. The goal is to best utilize or avoid currents, without limitation on these currents or on the number of vehicles. The methodology employs a new modified level set equation to evolve a front from the starting point of a vehicle until it reaches the desired goal location, combining flow advection with nominal vehicle motion. The optimal path of the vehicle is then obtained by solving a particle tracking equation backward in time. The computational cost of this method increases linearly with the number of vehicles and geometrically with spatial dimensions. The methodology is applicable to any continuous flow and in scenarios with multiple vehicles. Present illustrations consist of the crossing of a canonical uniform jet and its validation using a classic optimization solution, as well as swarm formation in more complex time varying 2D flow fields, including jets, eddies and forbidden regions.
Provably Safe Navigation for Mobile Robots with Limited Field-Of-Views in Unknown Dynamic EnvironmentsThis paper addresses the problem of navigating a mobile robot with a limited field-of-view in a unknown dynamic environment. In such a situation, absolute motion safety, i.e. such that no collision will ever take place whatever happens, is impossible to guarantee. It is therefore settled for a weaker level of motion safety dubbed passive motion safety: it guarantees that, if a collision takes place, the robot will be at rest. Passive motion safety is tackled using a variant of the Inevitable Collision State (ICS) concept called Braking ICS, i.e. states such that, whatever the future braking trajectory of the robot, a collision occurs before it is at rest. Passive motion safety is readily obtained by avoiding Braking ICS at all times. Building upon an existing Braking ICS-Checker, i.e. an algorithm that checks if a given state is a Braking ICS or not, this paper presents a reactive collision avoidance scheme called PassAvoid. The main contribution of this paper is the formal proof of PassAvoid's passive motion safety. Experiments in simulation demonstrates how PassAvoid operates.
An Efficient Mobile Robot Path Planning Using Hierarchical Roadmap Representation in Indoor EnvironmentThis paper describes a practical approach to solve a path planning problem in a home environment. The proposed approach incrementally constructs the hierarchical roadmap which has a multi-layered structure using a sonar grid map when a mobile robot navigates in unexplored area. The hierarchical roadmap can almost completely cover the traversable areas in the environment. The mobile robot path planner using the hierarchical roadmap can efficiently search for appropriate paths under the limited computing power and time by reducing the search space size. The benefits of the hierarchical roadmap representation were verified by experiments in a home environment.
3D Time-Space Path Planning Algorithm in Dynamic Environment Utilizing Arrival Time Field and Heuristically Randomized TreeThis paper deals with a path planning problem in the dynamic and cluttered environments. The presence of moving obstacles and kinodynamic constraints of the robot increases the complexity of path planning problem. We model the environment and motion of dynamic obstacles in <i>3D time-space</i>. We propose the utilization of <i>the arrival time field</i> for examining the most promising area in those <i>obstacles-occupied</i> 3D time-space for approaching the goal. The arrival time field is used for guiding the expansion of a randomized tree search in a favorable way, considering kinodynamic constraints of the robot. The quality and the optimality of the path are taken into account by performing heuristic methods on the randomized tree. Simulation results are also provided to prove the feasibility, possibility, and effectiveness of our algorithm.
High-Speed Navigation of a Uniformly Braking Mobile Robot Using Position-Velocity Configuration SpaceThis paper considers the problem of fast autonomous mobile robot navigation between obstacles while attempting to maximize velocity subject to safe braking constraints. The paper introduces position-velocity configuration space. Within this space, keeping a uniform braking distance from the obstacles can be modeled as forbidden regions called vc-obstacles. Using Morse Theory, the paper characterizes the critical position-velocity points where two vc-obstacles meet and locally disconnect the free position-velocity space. These points correspond to critical events where the robot's velocity becomes too large to support safe passage between neighboring obstacles. The velocity dependent critical points induce a cellular decomposition of the free position-velocity space into cells. Each cell is associated with a particular range of velocities that can be safely followed by the robot. The paper proposes a practical algorithm that searches the cells' adjacency graph for a maximum velocity path. The algorithm outputs a pseudo time optimal path which maintains safe braking distance from the obstacles throughout the robot motion. Simulations demonstrate the algorithm and highlight the usefulness of taking the path's velocity into account during the path planning process.