10,309 research outputs found
Human Motion Trajectory Prediction: A Survey
With growing numbers of intelligent autonomous systems in human environments,
the ability of such systems to perceive, understand and anticipate human
behavior becomes increasingly important. Specifically, predicting future
positions of dynamic agents and planning considering such predictions are key
tasks for self-driving vehicles, service robots and advanced surveillance
systems. This paper provides a survey of human motion trajectory prediction. We
review, analyze and structure a large selection of work from different
communities and propose a taxonomy that categorizes existing methods based on
the motion modeling approach and level of contextual information used. We
provide an overview of the existing datasets and performance metrics. We
discuss limitations of the state of the art and outline directions for further
research.Comment: Submitted to the International Journal of Robotics Research (IJRR),
37 page
Aerial Vehicles
This book contains 35 chapters written by experts in developing techniques for making aerial vehicles more intelligent, more reliable, more flexible in use, and safer in operation.It will also serve as an inspiration for further improvement of the design and application of aeral vehicles. The advanced techniques and research described here may also be applicable to other high-tech areas such as robotics, avionics, vetronics, and space
A Survey on Passing-through Control of Multi-Robot Systems in Cluttered Environments
This survey presents a comprehensive review of various methods and algorithms
related to passing-through control of multi-robot systems in cluttered
environments. Numerous studies have investigated this area, and we identify
several avenues for enhancing existing methods. This survey describes some
models of robots and commonly considered control objectives, followed by an
in-depth analysis of four types of algorithms that can be employed for
passing-through control: leader-follower formation control, multi-robot
trajectory planning, control-based methods, and virtual tube planning and
control. Furthermore, we conduct a comparative analysis of these techniques and
provide some subjective and general evaluations.Comment: 18 pages, 19 figure
Motion Planning for Autonomous Ground Vehicles Using Artificial Potential Fields: A Review
Autonomous ground vehicle systems have found extensive potential and
practical applications in the modern world. The development of an autonomous
ground vehicle poses a significant challenge, particularly in identifying the
best path plan, based on defined performance metrics such as safety margin,
shortest time, and energy consumption. Various techniques for motion planning
have been proposed by researchers, one of which is the use of artificial
potential fields. Several authors in the past two decades have proposed various
modified versions of the artificial potential field algorithms. The variations
of the traditional APF approach have given an answer to prior shortcomings.
This gives potential rise to a strategic survey on the improved versions of
this algorithm. This study presents a review of motion planning for autonomous
ground vehicles using artificial potential fields. Each article is evaluated
based on criteria that involve the environment type, which may be either static
or dynamic, the evaluation scenario, which may be real-time or simulated, and
the method used for improving the search performance of the algorithm. All the
customized designs of planning models are analyzed and evaluated. At the end,
the results of the review are discussed, and future works are proposed
Cooperative trajectory planning algorithm of USV-UAV with hull dynamic constraints
Efficient trajectory generation in complex dynamic environment stills remains
an open problem in the unmanned surface vehicle (USV) domain. In this paper, a
cooperative trajectory planning algorithm for the coupled USV-UAV system is
proposed, to ensure that USV can execute safe and smooth path in the process of
autonomous advance in multi obstacle maps. Specifically, the unmanned aerial
vehicle (UAV) plays the role as a flight sensor, and it provides real-time
global map and obstacle information with lightweight semantic segmentation
network and 3D projection transformation. And then an initial obstacle
avoidance trajectory is generated by a graph-based search method. Concerning
the unique under-actuated kinematic characteristics of the USV, a numerical
optimization method based on hull dynamic constraints is introduced to make the
trajectory easier to be tracked for motion control. Finally, a motion control
method based on NMPC with the lowest energy consumption constraint during
execution is proposed. Experimental results verify the effectiveness of whole
system, and the generated trajectory is locally optimal for USV with
considerable tracking accuracy.Comment: 10 pages, 9 figure
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