817 research outputs found
Combining Subgoal Graphs with Reinforcement Learning to Build a Rational Pathfinder
In this paper, we present a hierarchical path planning framework called SG-RL
(subgoal graphs-reinforcement learning), to plan rational paths for agents
maneuvering in continuous and uncertain environments. By "rational", we mean
(1) efficient path planning to eliminate first-move lags; (2) collision-free
and smooth for agents with kinematic constraints satisfied. SG-RL works in a
two-level manner. At the first level, SG-RL uses a geometric path-planning
method, i.e., Simple Subgoal Graphs (SSG), to efficiently find optimal abstract
paths, also called subgoal sequences. At the second level, SG-RL uses an RL
method, i.e., Least-Squares Policy Iteration (LSPI), to learn near-optimal
motion-planning policies which can generate kinematically feasible and
collision-free trajectories between adjacent subgoals. The first advantage of
the proposed method is that SSG can solve the limitations of sparse reward and
local minima trap for RL agents; thus, LSPI can be used to generate paths in
complex environments. The second advantage is that, when the environment
changes slightly (i.e., unexpected obstacles appearing), SG-RL does not need to
reconstruct subgoal graphs and replan subgoal sequences using SSG, since LSPI
can deal with uncertainties by exploiting its generalization ability to handle
changes in environments. Simulation experiments in representative scenarios
demonstrate that, compared with existing methods, SG-RL can work well on
large-scale maps with relatively low action-switching frequencies and shorter
path lengths, and SG-RL can deal with small changes in environments. We further
demonstrate that the design of reward functions and the types of training
environments are important factors for learning feasible policies.Comment: 20 page
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
Open-Source, Cost-Aware Kinematically Feasible Planning for Mobile and Surface Robotics
This paper introduces the Smac Planner, an openly available search-based
planning framework with multiple algorithm implementations including 2D-A*,
Hybrid-A*, and State Lattice planners. This work is motivated by the lack of
performant and available feasible planners for mobile and surface robotics
research.
This paper contains three main contributions. First, it briefly describes a
minimal open-source software framework where search-based planners may be
easily added. Further, this paper characterizes new variations on the feasible
planners - dubbed Cost-Aware - specific to mobile roboticist's needs. This
fills the gap of missing kinematically feasible implementations suitable for
academic, extension, and deployed use. Finally, we provide baseline
benchmarking against other standard planning frameworks.
Smac Planner has further significance by becoming the standard open-source
planning system within ROS 2's Nav2 framework which powers thousands of robots
in research and industry
An Open-Source 7-Axis, Robotic Platform to Enable Dexterous Procedures within CT Scanners
This paper describes the design, manufacture, and performance of a highly
dexterous, low-profile, 7 Degree-of-Freedom (DOF) robotic arm for CT-guided
percutaneous needle biopsy. Direct CT guidance allows physicians to localize
tumours quickly; however, needle insertion is still performed by hand. This
system is mounted to a fully active gantry superior to the patient's head and
teleoperated by a radiologist. Unlike other similar robots, this robot's fully
serial-link approach uses a unique combination of belt and cable drives for
high-transparency and minimal-backlash, allowing for an expansive working area
and numerous approach angles to targets all while maintaining a small in-bore
cross-section of less than . Simulations verified the system's
expansive collision free work-space and ability to hit targets across the
entire chest, as required for lung cancer biopsy. Targeting error is on average
on a teleoperated accuracy task, illustrating the system's sufficient
accuracy to perform biopsy procedures. The system is designed for lung biopsies
due to the large working volume that is required for reaching peripheral lung
lesions, though, with its large working volume and small in-bore
cross-sectional area, the robotic system is effectively a general-purpose
CT-compatible manipulation device for percutaneous procedures. Finally, with
the considerable development time undertaken in designing a precise and
flexible-use system and with the desire to reduce the burden of other
researchers in developing algorithms for image-guided surgery, this system
provides open-access, and to the best of our knowledge, is the first
open-hardware image-guided biopsy robot of its kind.Comment: 8 pages, 9 figures, final submission to IROS 201
Flexible Virtual Structure Consideration in Dynamic Modeling of Mobile Robots Formation
International audienceIn cooperative mobile robotics, we look for formation keeping and maintenance of a geometric configuration during movement. As a solution to these problems, the concept of a virtual structure is considered. Based on this idea, we have developed an efficient flexible virtual structure, describing the dynamic model of n vehicles in formation and where the whole formation is kept dependant. Notes that, for 2D and 3D space navigation, only a rigid virtual structure was proposed in the literature. Further, the problem was limited to a kinematic behavior of the structure. Hence, the flexible virtual structure in dynamic modeling of mobile robots formation presented in this paper, gives more capabilities to the formation to avoid obstacles in hostile environment while keeping formation and avoiding inter‐agent collision
- …