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Autonomous Driving -- 5 Years after the Urban Challenge: The Anticipatory Vehicle as a Cyber-Physical System
- PROCEEDINGS OF THE INFORMATIK
, 2012
"... ... promote the research and development on autonomously driving vehicles for urban environments. In the final race only eleven out of initially 89 competitors participated and “Boss” from Carnegie Mellon University succeeded. This paper summarizes results of the research carried out by all finalist ..."
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... promote the research and development on autonomously driving vehicles for urban environments. In the final race only eleven out of initially 89 competitors participated and “Boss” from Carnegie Mellon University succeeded. This paper summarizes results of the research carried out by all finalists within the last five years after the competition and provides an outlook where further investigation especially for software engineering is now necessary to achieve the goal of driving safely and reliably through urban environments with an anticipatory vehicle for the mass-market.
Safe distributed motion coordination for second-order systems with different planning cycles
- INTL J. OF ROBOTICS RESEARCH
, 2012
"... When multiple robots operate in the same environment, it is desirable for scalability purposes to coordinate their motion in a distributed fashion while providing guarantees about their safety. If the robots have to respect second-order dynamics, this becomes a challenging problem, even for static e ..."
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When multiple robots operate in the same environment, it is desirable for scalability purposes to coordinate their motion in a distributed fashion while providing guarantees about their safety. If the robots have to respect second-order dynamics, this becomes a challenging problem, even for static environments. This work presents a replanning framework where each robot computes partial plans during each cycle, while executing a previously computed trajectory. Each robot communicates with its neighbors to select a trajectory that is safe over an infinite time horizon. The proposed approach does not require synchronization and allows the robots to dynamically change their cycles over time. This paper proves that the proposed motion coordination algorithm guarantees safety under this general setting. This framework is not specific to the underlying robot dynamics, as it can be used with a variety of dynamical systems, nor to the planning or control algorithm used to generate the robot trajectories. The performance of the approach is evaluated using a distributed multi-robot simulator on a computing cluster, where the simulated robots are forced to communicate by exchanging messages. The simulation results confirm the safety of the algorithm in various environments with up to 32 robots governed by second-order dynamics.
Multi-heuristic A
- In Proceedings of Robotics: Science and Systems
, 2014
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Cost-based heuristic search is sensitive to the ratio of operator costs
- In Proceedings of the Forth Annual Symposium on Combinatorial Search, SOCS 2012
, 2011
"... Abstract In many domains, different actions have different costs. In this paper, we show that various kinds of best-first search algorithms are sensitive to the ratio between the lowest and highest operator costs. First, we take common benchmark domains and show that when we increase the ratio of o ..."
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Abstract In many domains, different actions have different costs. In this paper, we show that various kinds of best-first search algorithms are sensitive to the ratio between the lowest and highest operator costs. First, we take common benchmark domains and show that when we increase the ratio of operator costs, the number of node expansions required to find a solution increases. Second, we provide a theoretical analysis showing one reason this phenomenon occurs. We also discuss additional domain features that can cause this increased difficulty. Third, we show that searching using distance-togo estimates can significantly ameliorate this problem. Our analysis takes an important step toward understanding algorithm performance in the presence of differing costs. This research direction will likely only grow in importance as heuristic search is deployed to solve real-world problems.
DIFFERENTIALLY CONSTRAINED MOTION PLANNING WITH STATE LATTICE MOTION PRIMITIVES
, 2012
"... Robot motion planning with differential constraints has received a great deal of attention in the last few decades, yet it still remains a challenging problem. Among a number of reasons, three stand out. First, the differential constraints that most physical robots exhibit render the coupling betwee ..."
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Cited by 5 (0 self)
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Robot motion planning with differential constraints has received a great deal of attention in the last few decades, yet it still remains a challenging problem. Among a number of reasons, three stand out. First, the differential constraints that most physical robots exhibit render the coupling between the control and state spaces quite complicated. Second, it is commonly accepted that robots must be able to operate in environments that are partially or entirely unknown; classical motion planning techniques that assume known structure of the world frequently encounter difficulties when applied in this setting. Third, such robots are typically expected to operate with speed that is commensurate with that of humans. This poses stringent limitations on available runtime and often hard real-time requirements on the motion planner. The impressive advances in computing capacity in recent years have been unable, by themselves, to meet the computational challenge of this problem. New algorithmic approaches to tackle its difficulties continue to be developed to this day. The approach advocated in this thesis is based on encapsulating some of the complexity of satisfying the differential constraints in pre-computed controls that serve as motion primitives, elementary motions that are combined to form the solution trajectory for the system. The contribution of this work is in developing a general approach to constructing such motion primitives,
Generalized FringeRetrieving A*: Faster moving target search on state lattices.
- In Proc. of AAMAS,
, 2010
"... ABSTRACT Moving target search is important for robotics applications where unmanned ground vehicles (UGVs) have to follow other friendly or hostile UGVs. Artificial intelligence researchers have recently used incremental search to speed up the computation of a simple strategy for the hunter. The fa ..."
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ABSTRACT Moving target search is important for robotics applications where unmanned ground vehicles (UGVs) have to follow other friendly or hostile UGVs. Artificial intelligence researchers have recently used incremental search to speed up the computation of a simple strategy for the hunter. The fastest incremental search algorithm, Fringe-Retrieving A*, solves moving target search problems only on twodimensional grids, which are rather unrealistic models for robotics applications. We therefore generalize it to Generalized Fringe-Retrieving A*, which solves moving target search problems on arbitrary graphs, including the state lattices used for UGV navigation.
Real-time optimization-based planning in dynamic environments using gpus
- In ICRA ’13
, 2013
"... We present a novel algorithm to compute collision-free tra-jectories in dynamic environments. Our approach is general and makes no assumption about the obstacles or their motion. We use a replanning framework that interleaves optimization-based planning with execution. Furthermore, we describe a par ..."
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We present a novel algorithm to compute collision-free tra-jectories in dynamic environments. Our approach is general and makes no assumption about the obstacles or their motion. We use a replanning framework that interleaves optimization-based planning with execution. Furthermore, we describe a parallel formulation that exploits high number of cores on commodity graphics processors (GPUs) to compute a high-quality path in a given time interval. Overall, we show that search in configuration spaces can be significantly acceler-ated by using GPU parallelism.
Combining Space Exploration and Heuristic Search in Online Motion Planning for Nonholonomic Vehicles
"... Abstract — This paper presents an efficient motion planning method for nonholonomic vehicles, which combines space ex-ploration and heuristic search to achieve online performance. The space exploration employs simple geometric shapes to investigate the collision-free space for the dimension and topo ..."
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Abstract — This paper presents an efficient motion planning method for nonholonomic vehicles, which combines space ex-ploration and heuristic search to achieve online performance. The space exploration employs simple geometric shapes to investigate the collision-free space for the dimension and topology information. Then, the heuristic search is guided by this knowledge to generate vehicle motions under kinodynamic constraints. The overall performance of this framework greatly benefits from the cooperation of these two simple generic algo-rithms in suitable domains, which sequentially handles the free-space information and kinodynamic constraints. Experimental results show that this method is able to generate motions for nonholonomic vehicles in a time frame of less than 100 milliseconds for the given problem settings. The contribution of this work is the development of a Space Exploration Guided Heuristic Search with a circle-path based heuristics and adaptable search step size. The approach is grid-free and able to plan nonholonomic vehicle motions under kinodynamic constraints. I.
Optimal Acceleration-Bounded Trajectory Planning in Dynamic Environments Along a Specified Path
"... Abstract — Vehicles that cross lanes of traffic encounter the problem of navigating around dynamic obstacles under actuation constraints. This paper presents an optimal, exact, polynomial-time planner for optimal bounded-acceleration trajectories along a fixed, given path with dynamic obstacles. The ..."
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Abstract — Vehicles that cross lanes of traffic encounter the problem of navigating around dynamic obstacles under actuation constraints. This paper presents an optimal, exact, polynomial-time planner for optimal bounded-acceleration trajectories along a fixed, given path with dynamic obstacles. The planner constructs reachable sets in the path-velocity-time (PVT) space by propagating reachable velocity sets between obstacle tangent points in the path-time (PT) space. The terminal velocities attainable by endpoint-constrained trajectories in the same homotopy class are proven to span a convex interval, so the planner merges contributions from individual homotopy classes to find the exact range of reachable velocities and times at the goal. A reachability analysis proves that running time is polynomial given reasonable assumptions, and empirical tests demonstrate that it scales well in practice and can handle hundreds of dynamic obstacles in a fraction of a second on a standard PC. I.
A.: Anytime Motion Replanning in State lattices for Wheeled Robots
- In: Workshop on Physical Agents (WAF
, 2012
"... Abstract—Autonomous robots require robust and fast motion planning algorithms to operate in complex real environments. In the last years, motion planning in state lattices has emerged as a powerful paradigm to real time path planning taking into account the kinematic restrictions of the vehicle. The ..."
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Abstract—Autonomous robots require robust and fast motion planning algorithms to operate in complex real environments. In the last years, motion planning in state lattices has emerged as a powerful paradigm to real time path planning taking into account the kinematic restrictions of the vehicle. The approach requires the definition of the state lattice and the off-line calculation of the motion primitives. Therefore, motion planning is transformed into a search problem over a directed graph. In this paper, we apply the state lattice approach for motion planning of wheeled robots usign the AD * algorithm. Thus, the planning algorithm is anytime and dynamic, i.e., the path is improved incrementally and, also, the algorithm can replan. Results of different tests on a Pioneer P3-DX show the validity of the proposal. Index Terms—motion planning, state lattices, motion primi-tives, replanning, wheeled robots. I.
