64,524 research outputs found

    An Analytic Solution to Fixed-Time Point-to-Point Trajectory Planning

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    We derive an analytic solution to the problem of fixed-time trajectory generation with a quadratic cost function under velocity and acceleration constraints. This problem has a wide range of applications within motion planning. The advantage of the analytic solution compared to numerical optimization of the discretized problem is the unlimited resolution of the solution and the efficiency of the calculation, allowing sensor-based replanning and on-line trajectory generation

    Dynamic Modelling and Adaptive Traction Control for Mobile Robots

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    Mobile robots have received a great deal of research in recent years. A significant amount of research has been published in many aspects related to mobile robots. Most of the research is devoted to design and develop some control techniques for robot motion and path planning. A large number of researchers have used kinematic models to develop motion control strategy for mobile robots. Their argument and assumption that these models are valid if the robot has low speed, low acceleration and light load. However, dynamic modelling of mobile robots is very important as they are designed to travel at higher speed and perform heavy duty work. This paper presents and discusses a new approach to develop a dynamic model and control strategy for wheeled mobile robot which I modelled as a rigid body that roles on two wheels and a castor. The motion control strategy consists of two levels. The first level is dealing with the dynamic of the system and denoted as Low level controller. The second level is developed to take care of path planning and trajectory generation

    Point trajectory planning of flexible redundant robot manipulators using genetic algorithms

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    The paper focuses on the problem of point-to-point trajectory planning for flexible redundant robot manipulators (FRM) in joint space. Compared with irredundant flexible manipulators, a FRM possesses additional possibilities during point-to-point trajectory planning due to its kinematics redundancy. A trajectory planning method to minimize vibration and/or executing time of a point-to-point motion is presented for FRMs based on Genetic Algorithms (GAs). Kinematics redundancy is integrated into the presented method as planning variables. Quadrinomial and quintic polynomial are used to describe the segments that connect the initial, intermediate, and final points in joint space. The trajectory planning of FRM is formulated as a problem of optimization with constraints. A planar FRM with three flexible links is used in simulation. Case studies show that the method is applicable

    Search-based Motion Planning for Aggressive Flight in SE(3)

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    Quadrotors with large thrust-to-weight ratios are able to track aggressive trajectories with sharp turns and high accelerations. In this work, we develop a search-based trajectory planning approach that exploits the quadrotor maneuverability to generate sequences of motion primitives in cluttered environments. We model the quadrotor body as an ellipsoid and compute its flight attitude along trajectories in order to check for collisions against obstacles. The ellipsoid model allows the quadrotor to pass through gaps that are smaller than its diameter with non-zero pitch or roll angles. Without any prior information about the location of gaps and associated attitude constraints, our algorithm is able to find a safe and optimal trajectory that guides the robot to its goal as fast as possible. To accelerate planning, we first perform a lower dimensional search and use it as a heuristic to guide the generation of a final dynamically feasible trajectory. We analyze critical discretization parameters of motion primitive planning and demonstrate the feasibility of the generated trajectories in various simulations and real-world experiments.Comment: 8 pages, submitted to RAL and ICRA 201

    Trajectory generation for road vehicle obstacle avoidance using convex optimization

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    This paper presents a method for trajectory generation using convex optimization to find a feasible, obstacle-free path for a road vehicle. Consideration of vehicle rotation is shown to be necessary if the trajectory is to avoid obstacles specified in a fixed Earth axis system. The paper establishes that, despite the presence of significant non-linearities, it is possible to articulate the obstacle avoidance problem in a tractable convex form using multiple optimization passes. Finally, it is shown by simulation that an optimal trajectory that accounts for the vehicle’s changing velocity throughout the manoeuvre is superior to a previous analytical method that assumes constant speed
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