Add to ORKGThis paper describes a prototype robot grasping system that uses human grasping synergies and a self-organizing map to learn object affordances. The bio-inspired design of the system is presented as well as some of the results from affordance learning
Service robots are expected to autonomously and efficiently work in human-centric environments. For ...
Service robots are expected to autonomously and efficiently work in human-centric environments. For ...
This paper presents a novel object–object affordance learning approach that enables intelligent robo...
This paper describes a prototype robot grasping system that uses human grasping synergies and a self...
In this paper, we present an affordance learning system for robotic grasping. The system involves th...
In this paper, we present an affordance learning system for robotic grasping. The system involves th...
The capacity for learning to recognize and exploit environmental affordances is an im-portant consid...
A system is described which takes synergies extracted from human grasp experiments and maps these on...
A system is described which takes synergies extracted from human grasp experiments and maps these on...
One of the fundamental enabling mechanisms of human and animal intelligence, and equally, one of the...
One of the fundamental enabling mechanisms of human and animal intelligence, and equally, one of the...
International audienceTo be capable of lifelong learning in a real-life environment, robots have to ...
International audienceTo be capable of lifelong learning in a real-life environment, robots have to ...
International audienceTo be capable of lifelong learning in a real-life environment, robots have to ...
Service robots are expected to autonomously and efficiently work in human-centric environments. For ...
Service robots are expected to autonomously and efficiently work in human-centric environments. For ...
Service robots are expected to autonomously and efficiently work in human-centric environments. For ...
This paper presents a novel object–object affordance learning approach that enables intelligent robo...
This paper describes a prototype robot grasping system that uses human grasping synergies and a self...
In this paper, we present an affordance learning system for robotic grasping. The system involves th...
In this paper, we present an affordance learning system for robotic grasping. The system involves th...
The capacity for learning to recognize and exploit environmental affordances is an im-portant consid...
A system is described which takes synergies extracted from human grasp experiments and maps these on...
A system is described which takes synergies extracted from human grasp experiments and maps these on...
One of the fundamental enabling mechanisms of human and animal intelligence, and equally, one of the...
One of the fundamental enabling mechanisms of human and animal intelligence, and equally, one of the...
International audienceTo be capable of lifelong learning in a real-life environment, robots have to ...
International audienceTo be capable of lifelong learning in a real-life environment, robots have to ...
International audienceTo be capable of lifelong learning in a real-life environment, robots have to ...
Service robots are expected to autonomously and efficiently work in human-centric environments. For ...
Service robots are expected to autonomously and efficiently work in human-centric environments. For ...
Service robots are expected to autonomously and efficiently work in human-centric environments. For ...
This paper presents a novel object–object affordance learning approach that enables intelligent robo...