Abstract
Service robots are appearing more and more in our daily life. The development of service robots combines multiple fields of research, from object perception to object manipulation. The state-of-the-art continues to improve to make a proper coupling between object perception and manipulation. This coupling is necessary for service robots not only to perform various tasks in a reasonable amount of time but also to continually adapt to new environments and safely interact with non-expert human users. Nowadays, robots are able to recognize various objects, and quickly plan a collision-free trajectory to grasp a target object in predefined settings. Besides, in most of the cases, there is a reliance on large amounts of training data. Therefore, the knowledge of such robots is fixed after the training phase, and any changes in the environment require complicated, time-consuming, and expensive robot re-programming by human experts. Therefore, these approaches are still too rigid for real-life applications in unstructured environments, where a significant portion of the environment is unknown and cannot be directly sensed or controlled. In such environments, no matter how extensive the training data used for batch learning, a robot will always face new objects. Therefore, apart from batch learning, the robot should be able to continually learn about new object categories and grasp affordances from very few training examples on-site. Moreover, apart from robot self-learning, non-expert users could interactively guide the process of experience acquisition by teaching new concepts, or by correcting insufficient or erroneous concepts. In this way, the robot will constantly learn how to help humans in everyday tasks by gaining more and more experiences without the need for re-programming. In this paper, we review a set of previously published works and discuss advances in service robots from object perception to complex object manipulation and shed light on the current challenges and bottlenecks.
Highlights
The development of service robots, used for any domestic or service task, is ongoing and interest is growing
We mainly focus on object perception and object manipulation and do not cover the topic of simultaneous localization and mapping (SLAM) in mobile robots
We mainly focus on object perception and manipulation tasks in service robots with the distinctive characteristics of System 1
Summary
The development of service robots, used for any domestic or service task, is ongoing and interest is growing. There is an increase in supply, with ever more efficient and widely applicable robots. The old-age dependency ratio of the European population (i.e., people aged 65 or above relative to those aged 1564) was 29.6% in 2016 and is projected to reach 51.2% by 2070, meaning for every person in retirement age there are less than two people of working age.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have