140 research outputs found
Research and development at ORNL/CESAR towards cooperating robotic systems for hazardous environments
One of the frontiers in intelligent machine research is the understanding of how constructive cooperation among multiple autonomous agents can be effected. The effort at the Center for Engineering Systems Advanced Research (CESAR) at the Oak Ridge National Laboratory (ORNL) focuses on two problem areas: (1) cooperation by multiple mobile robots in dynamic, incompletely known environments; and (2) cooperating robotic manipulators. Particular emphasis is placed on experimental evaluation of research and developments using the CESAR robot system testbeds, including three mobile robots, and a seven-axis, kinematically redundant mobile manipulator. This paper summarizes initial results of research addressing the decoupling of position and force control for two manipulators holding a common object, and the path planning for multiple robots in a common workspace
Applying MAPP Algorithm for Cooperative Path Finding in Urban Environments
The paper considers the problem of planning a set of non-conflict
trajectories for the coalition of intelligent agents (mobile robots). Two
divergent approaches, e.g. centralized and decentralized, are surveyed and
analyzed. Decentralized planner - MAPP is described and applied to the task of
finding trajectories for dozens UAVs performing nap-of-the-earth flight in
urban environments. Results of the experimental studies provide an opportunity
to claim that MAPP is a highly efficient planner for solving considered types
of tasks
Navite: A Neural Network System For Sensory-Based Robot Navigation
A neural network system, NAVITE, for incremental trajectory generation and obstacle avoidance is presented. Unlike other approaches, the system is effective in unstructured environments. Multimodal inforrnation from visual and range data is used for obstacle detection and to eliminate uncertainty in the measurements. Optimal paths are computed without explicitly optimizing cost functions, therefore reducing computational expenses. Simulations of a planar mobile robot (including the dynamic characteristics of the plant) in obstacle-free and object avoidance trajectories are presented. The system can be extended to incorporate global map information into the local decision-making process.Defense Advanced Research Projects Agency (AFOSR 90-0083); Office of Naval Research (N00014-92-J-l309); Consejo Nacional de Ciencia y TecnologÃa (63l462
Timed Automata Approach for Motion Planning Using Metric Interval Temporal Logic
In this paper, we consider the robot motion (or task) planning problem under
some given time bounded high level specifications. We use metric interval
temporal logic (MITL), a member of the temporal logic family, to represent the
task specification and then we provide a constructive way to generate a timed
automaton and methods to look for accepting runs on the automaton to find a
feasible motion (or path) sequence for the robot to complete the task.Comment: Full Version for ECC 201
Game theoretic controller synthesis for multi-robot motion planning Part I : Trajectory based algorithms
We consider a class of multi-robot motion planning problems where each robot
is associated with multiple objectives and decoupled task specifications. The
problems are formulated as an open-loop non-cooperative differential game. A
distributed anytime algorithm is proposed to compute a Nash equilibrium of the
game. The following properties are proven: (i) the algorithm asymptotically
converges to the set of Nash equilibrium; (ii) for scalar cost functionals, the
price of stability equals one; (iii) for the worst case, the computational
complexity and communication cost are linear in the robot number
Any-Angle Pathfinding for Multiple Agents Based on SIPP Algorithm
The problem of finding conflict-free trajectories for multiple agents of
identical circular shape, operating in shared 2D workspace, is addressed in the
paper and decoupled, e.g., prioritized, approach is used to solve this problem.
Agents' workspace is tessellated into the square grid on which any-angle moves
are allowed, e.g. each agent can move into an arbitrary direction as long as
this move follows the straight line segment whose endpoints are tied to the
distinct grid elements. A novel any-angle planner based on Safe Interval Path
Planning (SIPP) algorithm is proposed to find trajectories for an agent moving
amidst dynamic obstacles (other agents) on a grid. This algorithm is then used
as part of a prioritized multi-agent planner AA-SIPP(m). On the theoretical,
side we show that AA-SIPP(m) is complete under well-defined conditions. On the
experimental side, in simulation tests with up to 200 agents involved, we show
that our planner finds much better solutions in terms of cost (up to 20%)
compared to the planners relying on cardinal moves only.Comment: Final version as submitted to ICAPS-2017 (main track); 8 pages; 4
figures; 1 algorithm; 2 table
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