Motion planning

About: Motion planning is a research topic. Over the lifetime, 32846 publications have been published within this topic receiving 553548 citations.

Time-energy optimal control of articulated systems with geometric path constraints

Abstract: A method is presented for optimizing the motions of articulated systems along specified paths, minimizing a time-energy cost function. Using a transformation to path variables, the optimization problem is formulated in a reduced two dimensional state space. The necessary conditions for optimality, stated for the reduced problem, lead to a compact two point boundary value problem that requires the iterations of only one boundary condition. The optimal control obtained for this problem is smooth, as opposed to the typically discontinuous time optimal control. The method is demonstrated numerically for a two link planar manipulator, and experimentally for the UCLA Direct Drive Arm. The smoother time-energy optimal trajectory is shown to result in smaller tracking errors than the time optimal trajectory. >

Identification and verification of termination conditions in fine motion in presence of sensor errors and geometric uncertainties

Abstract: The authors' long-term goal is to discover reasonable constraints under which an automatic uncertainty-handling strategy (for robot part-mating tasks) is guaranteed to succeed. As the first step they introduce a concept of contact formations to describe contacts among parts in a system, aiming at reducing the dimensionality of assembly verification. They also describe a technique for identifying contact formations in spite of errors in sensing and geometric uncertainties. It is impossible to verify termination conditions in general. The notion of design constraints is introduced, and design constraints for which verification can be guaranteed are formulated. The constraints are reasonable in the sense that they do not impose unrealistic conditions on typical designs. Results of implementation on a robot system consisting of PUMA robot with RTI force/torque sensors support the theoretical derivations and show empirically that the theoretical constraints can be relaxed somewhat and good results still be obtained. >

Fusion of Stereo-Camera and PMD-Camera Data for Real-Time Suited Precise 3D Environment Reconstruction

Abstract: 3D environment reconstruction is a basic task, delivering the data for mapping, localization and navigation in mobile robotics. We present a new technique that combines a stereo-camera system with a PMD-camera. Both systems generate distance images of the environment but with different characteristics. It is shown that each system compensates effectively for the deficiencies of the other one. The combined system is real-time suited. Experimental data of an indoor scene including the calibration procedure are reported.

Adaptive dynamic collision checking for single and multiple articulated robots in complex environments

Abstract: Static collision checking amounts to testing a given configuration of objects for overlaps. In contrast, the goal of dynamic checking is to determine whether all configurations along a continuous path are collision-free. While there exist effective methods for static collision detection, dynamic checking still lacks methods that are both reliable and efficient. A common approach is to sample paths at some fixed, prespecified resolution and statically test each sampled configuration. But this approach is not guaranteed to detect collision whenever one occurs, and trying to increase its reliability by refining the sampling resolution along the entire path results in slow checking. This paper introduces a new method for testing path segments in c-space or collections of such segments, that is both reliable and efficient. This method locally adjusts the sampling resolution by comparing lower bounds on distances between objects in relative motion with upper bounds on lengths of curves traced by points of these moving objects. Several additional techniques and heuristics increase the checker's efficiency in scenarios with many moving objects (e.g., articulated arms and/or multiple robots) and high geometric complexity. The new method is general, but particularly well suited for use in probabilistic roadmap (PRM) planners, where it is critical to determine as quickly as possible whether given path segments collide, or not. Extensive tests, in particular on randomly generated path segments and on multisegment paths produced by PRM planners, show that the new method compares favorably with a fixed-resolution approach at "suitable" resolution, with the enormous advantage that it never fails to detect collision.

Path Planning for Multi-UAV Formation

Abstract: This paper presents an efficient and feasible algorithm for the path planning problem of the multiple unmanned aerial vehicles (multi-UAVs) formation in a known and realistic environment. The artificial potential field method updated by the additional control force is used for establishing two models for the single UAV, which are the particle dynamic model and the path planning optimization model. The additional control force can be calculated by using the optimal control method. Furthermore, the multi-UAV path planning model is established by introducing "virtual velocity rigid body" and "virtual target point". Then, the motion states of the lead plane and wingmen are obtained from the path planning model. Finally, the path following process based on the quadrotor helicopter PID controllers is introduced to verify the rationality of the path planning results. The simulation results show that the artificial potential method with the additional control force improved by the optimal control method has a good path planning ability for the single UAV and the all UAVs formation. At the same time, the path planning results are available and the UAVs can basically track the UAV formation.