This paper presents a comprehensive unified control strategy for underactuated two-link manipulators, including acrobots and pendubots. The motion space is divided into two areas: swing-up and attractive; and control ...
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This paper presents a comprehensive unified control strategy for underactuated two-link manipulators, including acrobots and pendubots. The motion space is divided into two areas: swing-up and attractive; and control laws are designed for each. First, a control law based on a weak control Lyapunov function (WCLF) is employed to increase the energy and control the posture of the actuated link in the swing-up area. Next, one of the parameters of the WCLF is chosen to be a nonlinear function of the state so as to avoid any singularities. Then, another parameter in the control law is adjusted based on the state to improve the control performance. Stability is guaranteed in the swing-up area by the use of a WCLF based on the LaSalle invariant theorem. Finally, the global stability of the control system is guaranteed by the use of a non-smooth Lyapunov function integrated with a minimum-switching strategy. Simulation results for a pendubot and an acrobot show this control scheme to be very effective
This paper addresses the challenging problem of finding collision-free trajectories for many robots moving to individual goals within a common environment. Most popular algorithms for multi-robot planning manage the c...
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This paper addresses the challenging problem of finding collision-free trajectories for many robots moving to individual goals within a common environment. Most popular algorithms for multi-robot planning manage the complexity of the problem by planning trajectories for robots sequentially; such decoupled methods may fail to find a solution even if one exists. In contrast, this paper describes a multi-phase approach to the planning problem that guarantees a solution by creating and maintaining obstacle-free paths through the environment as required for each robot to reach its goal. Using a topological graph and spanning tree representation of a tunnel or corridor environment, the multi-phase planner is capable of planning trajectories for up to r = L – 1 robots, where the spanning tree includes L leaves. Monte Carlo simulations in a large environment with varying number of robots demonstrate that the algorithm can solve planning problems requiring complex coordination of many robots that cannot be solved with a decoupled approach, and is scalable with complexity linear in the number of robots.
This paper presents the design of a distributed sensing system that uses an Extended Kalman Filter (EKF) to fuse measurements, so that automotive vehicle states can be estimated for use by a Semi-active Suspension con...
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We have developed a generic ontology of objects, and a knowledge base of everyday physical objects. Objects are represented as assemblies of functional features and their spatial relations. Generic shape information o...
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Area-covering operation is a special kind of path planning, which requires the robot path to cover every part of the workspace. In this paper, a neural dynamics based algorithm is proposed for real-time map building a...
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Teleoperations are desirable when robots are not able to deal with a certain task autonomously. On the other hand, using mobile robots equipped with sensors provide a way to acquire the information in a hazardous envi...
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Fuzzy automata are proposed for fault diagnosis. The output of the monitored system is partitioned into linear segments which are assigned to pattern classes (templates) with the use of fuzzy membership functions. A s...
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In this paper, a novel fuzzy logic control system is developed for reactive navigation of a behavior-based mobile robot in dynamic environments. A combination of multiple sensors is equipped to sense the obstacles nea...
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In this paper, a novel fuzzy logic control system is developed for reactive navigation of a behavior-based mobile robot in dynamic environments. A combination of multiple sensors is equipped to sense the obstacles near the robot, the target location and the current robot speed. A fuzzy logic system with 48 fuzzy rules is designed, which consists of three behaviors: target seeking, obstacle avoidance and barrier following. The "symmetric indecision" problem is resolved by several mandatory-turn rules, while the "dead cycle" problem is resolved by a state memory strategy. Under the control of the proposed fuzzy logic model, the mobile robot can preferably "see" the environment around, and avoid static and moving obstacles automatically. The robot can generate reasonable trajectories toward the target in various situations without suffering from the "symmetric indecision" and the "dead cycle" problems. The effectiveness and efficiency of the proposed approach are demonstrated by simulation studies.
In this paper, visual information acquisition in vertebrate retina is investigated using a novel neural network model. The neural network is based on the neural anatomy and function of retinal neurons in tiger salaman...
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In this paper, visual information acquisition in vertebrate retina is investigated using a novel neural network model. The neural network is based on the neural anatomy and function of retinal neurons in tiger salamander and mudpuppy. All the main types of retinal neurons are modeled, and their response characteristics are studied. The objective is to model the information acquisition in vertebrate retina with a simple yet effective neural network architecture. The model predictions on the main characteristics of retinal neurons are in agreement with the neurophysiological data. This study not only offers insight into the biological strategy and mechanism on the early visual information acquisition in vertebrate retina, but also has potential industrial applications such as VLSI chip design for efficient visual and movement sensors.
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