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Aiming at the lack of stability and slow convergence of rapidly random-exploring trees (RRT) algorithm, an improved RRT path planning algorithm is proposed. Firstly, based on bidirectional search path planning algorithm, an improved combination strategy is proposed. The combination strategy combines target point search strategy with random search strategy, which not only improve the efficiency of...
It is necessary for a mobile robot to be able to efficiently plan a path from its starting, or current location to a desired goal location. This is a trivial task when the environment is static. However, the operational environment of the robot is rarely static, and it often has many moving obstacles. The robot may encounter one, or many of these unknown and unpredictable moving obstacles. The robot...
With the rapid development of e-commerce, warehousing and logistics industry has entered a period of rapid development. New logistics demand is not different from traditional commodity transport, with the features of small batches, variety, high speed and low cost. Flexible warehousing technology based on small mobile handing robots is rising rapidly. The article proposes a flexible warehouse space...
Multi robot path planning is a rising field in the zone of robotics because of its broad true applications like distribution center applications, pursuit and safeguard, military activities, and so forth. The significant favorable position of multi robot path planning is its simultaneousness, which is extremely helpful for reducing the time required for an operation. Coordination among different robots...
Sampling-based approaches constitute the state-of-the-art for robot motion planning. Collision checking and nearest neighbor search are the major performance bottlenecks of these methods. For an environment with fixed number of obstacles, collision checking for a new candidate state is a constant time operation, whereas nearest neighbor search usually degrades during the runtime of the algorithm....
We present a scalable robot motion planning algorithm for reach-avoid problems. We assume a discrete-time, linear model of the robot dynamics and a workspace described by a set of obstacles and a target region, where both the obstacles and the region are polyhedra. Our goal is to construct a trajectory, and the associated control strategy, that steers the robot from its initial point to the target...
This paper proposes a new model for robot navigation in dynamic environments. The robot learns the motions of the objects, does motion ahead predictions, and plans a collision-free path to the goal. In this paper two new predicting algorithms, based on the AprioriAll algorithm, and a planning algorithm, using a heuristic search, are proposed. A novel framework and a simulation environment were used...
In this work, we consider the labeled multi-robot planning problem. In this paradigm, a team of robots at fixed start positions must navigate to pre-specified and noninterchangable goal positions. While many algorithms have been proposed for finding optimal solutions to this problem, most methods assume that the robots are kinematic agents, whereas in reality, robots often have high-order dynamics...
The task of whole-body motion planning for humanoid robots is challenging due to its high-DOF nature, stability constraints, and the need for obstacle avoidance and movements that are efficient. Over the years, various approaches have been adopted to solve this problem such as bounding-box models and jacobian-based techniques. More commonly though, sampling-based algorithms are employed for this task...
Most existing path planning algorithms focus on generating piecewise linear functions, while the smoothness of the path is usually ignored. Route stability and energy saving are key issues for an autonomous underwater vehicle (AUV) working in the underwater environment. To ensure that AUV can pass through the target area steadily and safely, a path smoother is required. This paper puts forward a novel...
In various circumstances, planning at trajectory level is very useful to generate flexible collision-free motions for autonomous robots, especially when the system interacts with humans or human environment. This paper presents a simple and fast obstacle avoidance algorithm that operates at the trajectory level in real-time. The algorithm uses the Velocity Obstacle to obtain the boundary conditions...
We present a parallel Cartesian planning algorithm for redundant robot arms and manipulators. We pre-compute a roadmap, that takes into account static obstacles in the environment as well as singular configurations. At runtime, multiple paths in this roadmap are computed as initial trajectories for an optimization-based planner that tends to satisfy various constraints corresponding to demands on...
In this paper, a hybrid strategy based on interfered fluid dynamical system (IFDS) and improved rapidly-exploring random tree (IRRT) is proposed for the unmanned aerial vehicle (UAV) route planning problem in 3-dimensional complex environments. By imitating the phenomenon of fluid flow, the IFDS method can plan a smooth and safe path quickly, but the route may fall into the concave area produced by...
In our previous work [1] we introduced the Anticipative Kinodynamic Planning (AKP): a robot navigation algorithm in dynamic urban environments that seeks to minimize its disruption to nearby pedestrians. In the present paper, we maintain all the advantages of the AKP, and we overcome the previous limitations by presenting novel contributions to our approach. Firstly, we present a multi-objective cost...
Path planning of a mobile robot under dynamic environment is a difficult part of robot navigation. In this paper, a new path planning method based on improved Q-learning (IQL) algorithm and some heuristic searching strategies is proposed for mobile robot in dynamic environment. A new exploration strategy which combines ε-greedy exploration with Boltzmann exploration is used in IQL. In addition, the...
Path planning among obstacles for nonholonomic systems is a widely researched area nowadays, but it is still one of the most challenging problems in autonomous navigation. We have recently presented a rapidly exploring random tree based global planner (RTR) and a steering method (C*CS) for car-like vehicles, which uses circular and straight movements. With the aid of these two methods it is possible...
Highly dynamic environments pose a particular challenge for motion planning due to the need for constant evaluation or validation of plans. However, due to the wide range of applications, an algorithm to safely plan in the presence of moving obstacles is required. In this paper, we propose a novel technique that provides computationally efficient planning solutions in environments with static obstacles...
Asymptotically-optimal sampling-based motion planners, like RRT*, perform vast amounts of collision checking, and are hence rather slow to converge in complex problems where collision checking is relatively expensive. This paper presents two novel motion planners, Lazy-PRM* and Lazy-RRG*, that eliminate the majority of collision checks using a lazy strategy. They are sampling-based, any-time, and...
We present an algorithm that seeks to find a set of diverse, short paths through a roadmap graph. The usefulness of a such a set is illustrated in robotic motion planning and routing applications wherein a precomputed roadmap of the environment is partially invalidated by some change, for example, relocation of obstacles or reconfiguration of the robot. Our algorithm employs the heuristic that nearby...
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