First, distributed multidestination potential fields are developed that are able to drive every agent to any available destination. In this paper, we address this challenge using two novel ideas. In particular, in applications such as coverage by mobile sensor networks or multiple target tracking, a great new challenge is the development of motion planning algorithms that dynamically assign targets or destinations to multiple homogeneous agents, not relying on any a priori assignment of agents to destinations. The proposed algorithm has been implemented on a real forklift and the navigation of the forklift from an arbitrary initial configuration to a goal configuration while avoiding collisions has been demonstrated.ĭistributed motion planning of multiple agents raises fundamental and novel problems in control theory and robotics.
INMR FORKLIFT PARTS FREE
The effectiveness of the developed algorithm is illustrated through three simulations (three vehicles in a free environment, three vehicles in the presence of a static obstacle, and eight vehicles operating along a corridor) and two experiments (static and moving obstacles avoidance). The asymptotic stability of the closed-loop system is proved. As a Lyapunov function for deriving a smooth control law that drives all the vehicles from an initial configuration to a goal configuration, a new navigation function that incorporates the squared norm of the navigation variables, the boundaries of collision-free areas, and the angles made by the vehicle heading direction and the vehicle-to-obstacle (v-to-o) vectors is proposed. The position and orientation information of individual vehicles is transformed to navigation variables, which are the distance left to the goal position, the angle made by the orientation of the vehicle at the goal position and the vehicle-to-target (v-to-t) vector, and the angle made by the heading direction of the vehicle and the v-to-t vector. In this paper, a collision-free navigation method for a group of autonomous wheeled vehicles is investigated. We compare our time-extended approaches with a range of single task allocation approaches in a simulated disaster response domain. Our second method uses a centralized, non-heuristic, genetic algorithm-based approach that provides higher quality solutions but at substantially greater computational cost. Our first approach uses tiered auctions and two heuristic techniques, clustering and opportunistic path planning, to perform a bounded search of possible time-extended schedules and allocations. This work presents two methods for generating time-extended coordination solutions-solutions where more than one task is assigned to each agent-for domains with intra-path constraints. A high-quality coordination solution must determine not only a task allocation but also what routes the fire trucks should take given the intra-path precedence constraints and which bulldozers should be assigned to clear debris along those routes. The disaster has also caused many city roads to be blocked by impassable debris, which can be cleared by bulldozer robots. In this domain a group of fire truck agents attempt to address fires spread throughout a city in the wake of a large-scale disaster. This work focuses on multi-agent coordination for disaster response with intra-path precedence constraints, a compelling application that is not well addressed by current coordination methods. Among these domains are those in which successful coordination must respect intra-path constraints, which are constraints that occur on the paths of agents and affect route planning. Many applications require teams of robots to cooperatively execute tasks. Finally, simulation results are presented to demonstrate the validity of the theoretical development of the proposed designs for real-time teleoperation applications. The stability conditions are established in the presence of passive and constant human and environment interaction forces with the master and slave manipulators. Using Lyapunov-Krasovskii function, delay-dependent stability and tracking conditions for both teleoperators are developed in the presence of symmetrical and unsymmetrical time varying delays.
Then, we develop teleoperators by delaying position and velocity signals of the master and slave manipulator. The design also combined undelayed position and velocity signals with nonlinear adaptive control terms to deal with the parametric uncertainties associated with the dynamical model of the master and slave manipulator. We first design teleoperation systems where the local and remote sites are coupled by position signals of the master and slave manipulator.
In this paper, we introduce delay-dependent control strategies for bilateral teleoperation systems in the presence of passive and constant input forces under time varying delay.