A real-time trajectory modification algorithm

Robotica ◽  
2001 ◽  
Vol 19 (4) ◽  
pp. 395-405 ◽  
Author(s):  
Vadim Rogozin ◽  
Yael Edan ◽  
Tamar Flash
Keyword(s):  
Real Time ◽  
Target Location ◽  
Time Algorithm ◽  
Initial Position ◽  
Human Motion ◽  
Movement Direction ◽  
Switch Time ◽  
Velocity Constraints ◽  
The Mathematical Model ◽  
Motion Behavior

This paper presents a real-time algorithm for modifying the trajectory of a manipulator approaching a moving target. The algorithm is based on the superposition scheme; a model developed based on human motion behavior. The algorithm generates a smooth trajectory toward the new target by calculating the vectorial sum between the first trajectory (initial position and first target) and second trajectory (between first and second target location). The algorithm searches for the switch hme that will result in a minimum time trajectory. The idea of the algorithm is to define some domain where the optimal switching time can be found, reduce this domain as much as possible to decrease the number of the points that must be checked and try every remaining candidate in this domain to find numerically the best (optimal) switch time. The algorithm was implemented on an Adept-one robotic system taking into account velocity constraints. The actual velocity profile was found to be less smooth than specified by the mathematical model. When the switch occurs at the middle of the trajectory when the speed is close to its maximum, the change in the movement direction is performed more gently.

scholarly journals A Probabilistic Model for Real-Time Semantic Prediction of Human Motion Intentions from RGBD-Data

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4141
Author(s):  
Wouter Houtman ◽  
Gosse Bijlenga ◽  
Elena Torta ◽  
René van de Molengraft
Keyword(s):  
Real Time ◽  
Collision Avoidance ◽  
Probabilistic Model ◽  
Real Life ◽  
Human Motion ◽  
Model Based ◽  
Multiple Hypotheses ◽  
Navigation Algorithms ◽  
The Right ◽  
Motion Behavior

For robots to execute their navigation tasks both fast and safely in the presence of humans, it is necessary to make predictions about the route those humans intend to follow. Within this work, a model-based method is proposed that relates human motion behavior perceived from RGBD input to the constraints imposed by the environment by considering typical human routing alternatives. Multiple hypotheses about routing options of a human towards local semantic goal locations are created and validated, including explicit collision avoidance routes. It is demonstrated, with real-time, real-life experiments, that a coarse discretization based on the semantics of the environment suffices to make a proper distinction between a person going, for example, to the left or the right on an intersection. As such, a scalable and explainable solution is presented, which is suitable for incorporation within navigation algorithms.

Real-Time Forward Position Kinematics of the Spatial Parallel Manipulator

2013 ◽  
Vol 712-715 ◽  
pp. 2241-2248
Author(s):  
Jian Wei Mi ◽  
Li Du ◽  
Xue Chao Duan
Keyword(s):  
Real Time ◽  
High Precision ◽  
Parallel Manipulator ◽  
Jacobian Matrix ◽  
Parallel Manipulators ◽  
Time Algorithm ◽  
Initial Position ◽  
End Effector ◽  
Time Consumption ◽  
Online Implementation

Aiming at online implementation, a real-time algorithm for forward position kinematics of the parallel manipulators is proposed, in which the steepest decent direction of the solution iteration is constructed with Jacobian matrix, with the initial position for iteration arbitrarily chosen from the workspace. Under the condition of motion continuity of the end-effector, the unique forward position kinematics solution can be found out with this algorithm. Forward position kinematics case studies of spatial parallel manipulators were conducted, which show that the algorithm has the advantages of a high precision, little iteration and less millisecond-level time consumption.

scholarly journals A novel edge gradient algorithm for multiple mobile robots cooperative mapping in unknown environment

2019 ◽  
Vol 16 (4) ◽  
pp. 172988141986038
Author(s):  
Huang Yiqing ◽  
Wang Hui ◽  
Wei Lisheng ◽  
Gao Wengen ◽  
Ge Yuan
Keyword(s):  
Visual Field ◽  
Mobile Robots ◽  
Information Exchange ◽  
Field Of View ◽  
Gradient Algorithm ◽  
Movement Direction ◽  
Mapping Technique ◽  
Map Building ◽  
Multiple Mobile Robots ◽  
Motion Behavior

This article presented a cooperative mapping technique using a novel edge gradient algorithm for multiple mobile robots. The proposed edge gradient algorithm can be divided into four behaviors such as adjusting the movement direction, evaluating the safety of motion behavior, following behavior, and obstacle information exchange, which can effectively prevent multiple mobile robots falling into concave obstacle areas. Meanwhile, a visual field factor is constructed based on biological principles so that the mobile robots can have a larger field of view when moving away from obstacles. Also, the visual field factor will be narrowed due to the obstruction of the obstacle when approaching an obstacle and the obtained map-building data are more accurate. Finally, three sets of simulation and experimental results demonstrate the performance superiority of the presented algorithm.

A Distributed Real-Time Algorithm for Preference-Based Agreement

2011 ◽  
Vol 44 (1) ◽  
pp. 8933-8938
Author(s):  
Daniel Zelazo ◽  
Mathias Bürger ◽  
Frank Allgöwer
Keyword(s):  
Real Time ◽  
Time Algorithm

scholarly journals Real-Time Algorithm for Versatile Displacement Sensors Based on Self-Mixing Interferometry

2016 ◽  
Vol 16 (1) ◽  
pp. 195-202 ◽  
Author(s):  
Antonio Luna Arriaga ◽  
Francis Bony ◽  
Thierry Bosch
Keyword(s):  
Real Time ◽  
Time Algorithm ◽  
Displacement Sensors

An Efficient Smartphone Assisted Indoor Localization with Tracking Approach using Glowworm Swarm Optimization Algorithm

2021 ◽  
pp. 101-107
Author(s):  
Mohammad Alshehri ◽  
Keyword(s):  
Real Time ◽  
Indoor Localization ◽  
Initial Position ◽  
Swarm Optimization ◽  
The Real ◽  
Assisted Navigation ◽  
Glowworm Swarm Optimization ◽  
Tracking Process ◽  
Wide Range ◽  
Localization And Tracking

Presently, a precise localization and tracking process becomes significant to enable smartphone-assisted navigation to maximize accuracy in the real-time environment. Fingerprint-based localization is the commonly available model for accomplishing effective outcomes. With this motivation, this study focuses on designing efficient smartphone-assisted indoor localization and tracking models using the glowworm swarm optimization (ILT-GSO) algorithm. The ILT-GSO algorithm involves creating a GSO algorithm based on the light-emissive characteristics of glowworms to determine the location. In addition, the Kalman filter is applied to mitigate the estimation process and update the initial position of the glowworms. A wide range of experiments was carried out, and the results are investigated in terms of distinct evaluation metrics. The simulation outcome demonstrated considerable enhancement in the real-time environment and reduced the computational complexity. The ILT-GSO algorithm has resulted in an increased localization performance with minimal error over the recent techniques.

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