scholarly journals Ai Motion Control – A Generic Approach to Develop Control Policies for Robotic Manipulation Tasks

2019 ◽  
Vol 1 (1) ◽  
pp. 3561-3570 ◽  
Author(s):  
Philip Kurrek ◽  
Mark Jocas ◽  
Firas Zoghlami ◽  
Martin Stoelen ◽  
Vahid Salehi
Keyword(s):  
Motion Control ◽  
Robot Control ◽  
Autonomous Robots ◽  
Descriptive Study ◽  
Robotic Manipulation ◽  
Complex Environments ◽  
Control Policies ◽  
Time Motion ◽  
Research Gap ◽  
Industrial Use

AbstractCurrent robotic solutions are able to manage specialized tasks, but they cannot perform intelligent actions which are based on experience. Autonomous robots that are able to succeed in complex environments like production plants need the ability to customize their capabilities. With the usage of artificial intelligence (AI) it is possible to train robot control policies without explicitly programming how to achieve desired goals. We introduce AI Motion Control (AIMC) a generic approach to develop control policies for diverse robots, environments and manipulation tasks. For safety reasons, but also to save investments and development time, motion control policies can first be trained in simulation and then transferred to real applications. This work uses the descriptive study I according to Blessing and Chakrabarti and is about the identification of this research gap. We combine latest motion control and reinforcement learning results and show the potential of AIMC for robotic technologies with industrial use cases.

Motion Analysis of Human Lifting Works with Heavy Objects

2005 ◽  
Vol 17 (6) ◽  
pp. 628-635 ◽  
Author(s):  
Nobutomo Matsunaga ◽  
◽  
Shigeyasu Kawaji
Keyword(s):  
Motion Control ◽  
Motion Analysis ◽  
Real World ◽  
Control Strategy ◽  
Robot Control ◽  
Autonomous Robots ◽  
Biped Robot ◽  
Weight Lifting ◽  
The Real ◽  
Lower Back

Advances in robot development involves autonomous work in the real world, where robots may lift or carry heavy objects. Motion control of autonomous robots is an important issue, in which configurations and motion differ depending on the robot and the object. Isaka et al. analyzed that lifting configuration is important in realizing efficient lifting minimizing the burden on the lower back, but their analysis was limited to weight lifting of a fixed object. Biped robot control requires analyzing different lifting in diverse situations. Thus, motion analysis is important in clarifying control strategy. We analyzed dynamics of human lifting of barbells in different situations, and found that lifting can be divided into four motions.

Evaluating probabilistic model checking tools for verification of robot control policies

2016 ◽  
Vol 29 (2) ◽  
pp. 287-299 ◽  
Author(s):  
Shashank Pathak ◽  
Luca Pulina ◽  
Armando Tacchella
Keyword(s):  
Model Checking ◽  
Probabilistic Model ◽  
Robot Control ◽  
Probabilistic Model Checking ◽  
Control Policies

scholarly journals Motivation as a tool for designing lifelong learning robots

2020 ◽  
Vol 27 (4) ◽  
pp. 353-372
Author(s):  
Alejandro Romero ◽  
Francisco Bellas ◽  
José A. Becerra ◽  
Richard J. Duro
Keyword(s):  
Robot Control ◽  
Control Structure ◽  
Autonomous Robots ◽  
Point Of View ◽  
Main Question ◽  
Structured Design ◽  
Design Time ◽  
Real Robot ◽  
Series Of Experiments ◽  
Definition Of

Designing robots has usually implied knowing beforehand the tasks to be carried out and in what domains. However, in the case of fully autonomous robots this is not possible. Autonomous robots need to operate in an open-ended manner, that is, deciding on the most interesting goals to achieve in domains that are not known at design time. This obviously poses a challenge from the point of view of designing the robot control structure. In particular, the main question that arises is how to endow the robot with a designer defined purpose and with means to translate that purpose into operational decisions without any knowledge of what situations the robot will find itself in. In this paper, we provide a formalization of motivation from an engineering perspective that allows for the structured design of purposeful robots. This formalization is based on a definition of the concepts of robot needs and drives, which are related through experience to the appropriate goals in specific domains. To illustrate the process, a motivational system to guide the operation of a real robot is constructed using this approach. A series of experiments carried out over it are discussed providing some insights on the design of purposeful motivated operation.

scholarly journals Real-Time Motion Control for Safe Navigation

1998 ◽  
Vol 31 (3) ◽  
pp. 303-308 ◽  
Author(s):  
R. Fernández ◽  
A. Mandow ◽  
V.F. Muãoz ◽  
A. García-Cerezo
Keyword(s):  
Real Time ◽  
Motion Control ◽  
Safe Navigation ◽  
Time Motion
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