Grant: Discovery Grants Program - Individual
University of Ontario Institute of Technology
$21,000.00
Research and Development of Visual Perception and Manipulation in an Interactive Autonomous Robotic System
FY 2018-19
Summary
The proposed proposal for the program is to develop methodologies and technologies that will lead to precise manipulation of autonomous mobile robots in practical applications with dynamic interaction. The main contribution is set to improve the versatility, autonomy and dependability of current autonomous robotic systems, specifically in manipulation applications. In view of the needed capabilities for the ultimate objective, the scope of the proposed program spans four main research areas: 1. Machine vision, specifically real-time and robust object tracking and hand gesture understanding 2. Advanced force, tactile and vision control, 3. Machine learning, and 4. Sensor fusion. An overall architecture is proposed, containing three sub-systems: 1). Efficient visual tracking and motion estimation; 2). Interaction framework; and 3). Advanced control in manipulation. *In the proposed architecture, the efficient visual tracking provides real-time and robust object tracking and motion estimation results to the vision-based control. The proposed interaction framework contains a knowledge base that describes tasks, and a high-level interpreter that can provide references for pose, force and tactile information in a given task. Also, an advanced control system will be developed, which will achieve the alignment of hand with respect to the object according to the suggested pose by the high-level task interpreter, and a position-force-tactile controller to provide robust and stable manipulation during the contact. *The proposed program will lead to innovative interaction framework for an autonomous robotic system in manipulation, efficient optical tracking in motion and motion estimation, and human-like-manipulation by developing an advanced position-force-tactile controller with an interaction framework. The research results in the proposed program will have significant potential for application in many practical areas including search and rescue, homecare and assistive robots. The developed intelligent autonomous robots are applicable in industry and in daily life, leading to improved work efficiency, reduced workload for humans, and effective execution of tasks that require heavy duty machinery. The developed technologies are expected to result in significant progress in robotics research, particularly concerning perception, interaction and manipulation, and provide new research directions in autonomous robotics.
Program
Discovery Grants Program - Individual
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
RGPIN-2017-05762
Name nom
Lang, Haoxiang
Department département
Engineering and Applied Science, Faculty of
Organization id
19222
Institution établissement
University of Ontario Institute of Technology
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2018
Competition year année de concours
2017
Award amount
21000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
Discovery grants programs
Group fr
Programmes de subventions à la découverte
Committee code
1512
Committee name en
Mechanical Engineering
Committee name fr
Génie mécanique
Area of application code
1206
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Engineering
Area of application fr
Génie
Research subject code
2601
Research subject group en
Robotics
Research subject group fr
Robotique
Research subject en
Robotic control
Research subject fr
Systèmes de commande
Partie
2
Nb partie
5
Application title
Research and Development of Visual Perception and Manipulation in an Interactive Autonomous Robotic System
Keyword
NSERC
Application summary
The proposed proposal for the program is to develop methodologies and technologies that will lead to precise manipulation of autonomous mobile robots in practical applications with dynamic interaction. The main contribution is set to improve the versatility, autonomy and dependability of current autonomous robotic systems, specifically in manipulation applications. In view of the needed capabilities for the ultimate objective, the scope of the proposed program spans four main research areas: 1. Machine vision, specifically real-time and robust object tracking and hand gesture understanding 2. Advanced force, tactile and vision control, 3. Machine learning, and 4. Sensor fusion. An overall architecture is proposed, containing three sub-systems: 1). Efficient visual tracking and motion estimation; 2). Interaction framework; and 3). Advanced control in manipulation. *In the proposed architecture, the efficient visual tracking provides real-time and robust object tracking and motion estimation results to the vision-based control. The proposed interaction framework contains a knowledge base that describes tasks, and a high-level interpreter that can provide references for pose, force and tactile information in a given task. Also, an advanced control system will be developed, which will achieve the alignment of hand with respect to the object according to the suggested pose by the high-level task interpreter, and a position-force-tactile controller to provide robust and stable manipulation during the contact. *The proposed program will lead to innovative interaction framework for an autonomous robotic system in manipulation, efficient optical tracking in motion and motion estimation, and human-like-manipulation by developing an advanced position-force-tactile controller with an interaction framework. The research results in the proposed program will have significant potential for application in many practical areas including search and rescue, homecare and assistive robots. The developed intelligent autonomous robots are applicable in industry and in daily life, leading to improved work efficiency, reduced workload for humans, and effective execution of tasks that require heavy duty machinery. The developed technologies are expected to result in significant progress in robotics research, particularly concerning perception, interaction and manipulation, and provide new research directions in autonomous robotics.