11,837 research outputs found
On-orbit assembly using superquadric potential fields
The autonomous on-orbit assembly of a large space structure is presented using a method based on superquadric artificial potential fields. The final configuration of the elements which form the structure is represented as the minimum of some attractive potential field. Each element of the structure is then considered as presenting an obstacle to the others using a superquadric potential field attached to the body axes of the element. A controller is developed which ensures that the global potential field decreases monotonically during the assembly process. An error quaternion representation is used to define both the attractive and superquadric obstacle potentials allowing the final configuration of the elements to be defined through both relative position and orientation. Through the use of superquadric potentials, a wide range of geometric objects can be represented using a common formalism, while collision avoidance can make use of both translational and rotation maneuvers to reduce total maneuver cost for the assembly process
Zero-gravity movement studies
The use of computer graphics to simulate the movement of articulated animals and mechanisms has a number of uses ranging over many fields. Human motion simulation systems can be useful in education, medicine, anatomy, physiology, and dance. In biomechanics, computer displays help to understand and analyze performance. Simulations can be used to help understand the effect of external or internal forces. Similarly, zero-gravity simulation systems should provide a means of designing and exploring the capabilities of hypothetical zero-gravity situations before actually carrying out such actions. The advantage of using a simulation of the motion is that one can experiment with variations of a maneuver before attempting to teach it to an individual. The zero-gravity motion simulation problem can be divided into two broad areas: human movement and behavior in zero-gravity, and simulation of articulated mechanisms
Towards building a team of intelligent robots
Topics addressed include: collision-free motion planning of multiple robot arms; two-dimensional object recognition; and pictorial databases (storage and sharing of the representations of three-dimensional objects)
Modeling Cooperative Navigation in Dense Human Crowds
For robots to be a part of our daily life, they need to be able to navigate
among crowds not only safely but also in a socially compliant fashion. This is
a challenging problem because humans tend to navigate by implicitly cooperating
with one another to avoid collisions, while heading toward their respective
destinations. Previous approaches have used hand-crafted functions based on
proximity to model human-human and human-robot interactions. However, these
approaches can only model simple interactions and fail to generalize for
complex crowded settings. In this paper, we develop an approach that models the
joint distribution over future trajectories of all interacting agents in the
crowd, through a local interaction model that we train using real human
trajectory data. The interaction model infers the velocity of each agent based
on the spatial orientation of other agents in his vicinity. During prediction,
our approach infers the goal of the agent from its past trajectory and uses the
learned model to predict its future trajectory. We demonstrate the performance
of our method against a state-of-the-art approach on a public dataset and show
that our model outperforms when predicting future trajectories for longer
horizons.Comment: Accepted at ICRA 201
Safe Local Exploration for Replanning in Cluttered Unknown Environments for Micro-Aerial Vehicles
In order to enable Micro-Aerial Vehicles (MAVs) to assist in complex,
unknown, unstructured environments, they must be able to navigate with
guaranteed safety, even when faced with a cluttered environment they have no
prior knowledge of. While trajectory optimization-based local planners have
been shown to perform well in these cases, prior work either does not address
how to deal with local minima in the optimization problem, or solves it by
using an optimistic global planner.
We present a conservative trajectory optimization-based local planner,
coupled with a local exploration strategy that selects intermediate goals. We
perform extensive simulations to show that this system performs better than the
standard approach of using an optimistic global planner, and also outperforms
doing a single exploration step when the local planner is stuck. The method is
validated through experiments in a variety of highly cluttered environments
including a dense forest. These experiments show the complete system running in
real time fully onboard an MAV, mapping and replanning at 4 Hz.Comment: Accepted to ICRA 2018 and RA-L 201
Collision-free motion of two robot arms in a common workspace
Collision-free motion of two robot arms in a common workspace is investigated. A collision-free motion is obtained by detecting collisions along the preplanned trajectories using a sphere model for the wrist of each robot and then modifying the paths and/or trajectories of one or both robots to avoid the collision. Detecting and avoiding collisions are based on the premise that: preplanned trajectories of the robots follow a straight line; collisions are restricted to between the wrists of the two robots (which corresponds to the upper three links of PUMA manipulators); and collisions never occur between the beginning points or end points on the straight line paths. The collision detection algorithm is described and some approaches to collision avoidance are discussed
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