Towards Automatic Manipulation Action Planning for Service Robots

Mao

International Journal of Advanced Robotic Systems

et al. 2017

To support robust plan execution of autonomous robots in dynamic environments, autonomous robot software should include adaptive and reactive capabilities to cope with the dynamics and uncertainties of the evolving states of real-world environments. However, conventional software architectures such as sense-model-plan-act and behaviour-based paradigms are inadequate for meeting the requirements. A lack of sensing during acting in the sense-model-plan-act paradigm makes the software slow to react to run-time contingencies, whereas the behaviour-based architectures typically fall short in planning of long-range steps and making optimized plan adaptations. This article proposes a hybrid software architecture that maintains both adaptivity and reactivity of robot behaviours in dynamic environments. To implement this architecture, we further present the multi-agent development framework known as AutoRobot, which views the robot software as a multi-agent system in which diverse agent roles collaborate to achieve software functionalities. To demonstrate the applicability and validity of our concrete framework and software architecture, we conduct an experiment to implement a typical case, for example, a robot that autonomously picks up and drops off dishes for remote guests, which requires the robot to plan and navigate in a highly dynamic environment and can adapt its behaviours to unexpected situations.

Section: Related Workmentioning

confidence: 99%

Towards a hybrid software architecture and multi-agent approach for autonomous robot software

Mao

International Journal of Advanced Robotic Systems

et al. 2017

2012 IEEE International Conference on Robotics and Automation

“…III-A, segmentation of manipulation is necessary in order to generate useful time invariant features. In order to adapt the course of actions in a flexible manner, we use a high-level symbolic description, which is mapped in an event based manner to parameters for the impedance control [17]. Therefore, activities are decomposed into atomic actions, which have constant control parameters.…”

Section: Segmentationmentioning

confidence: 99%

Monitoring of manipulation activities for a service robot using supervised learning

Ruehl

Xue

Dillmann

2012

Self Cite

To be a good helper, grasping and manipulation are the most important abilities of a service robot. It should be able to adapt its manipulation actions to new tasks and environments. During the execution, it is important to rate the success of actions, so that the robot can plan and execute further actions to correct and recover from the failed actions.The successful execution of manipulation actions depends on various factors during the whole execution, such as the position of the robotic hand and forces exerted by the robot. The goal of the manipulation action monitoring is to estimate the sucess state from the huge amount of data collected during the execution. The main challenge to solve this problem is to identify the success or failure state from the the high dimensional data collection.We propose a method to classify ongoing activities using a set of support vector machines (SVM). After a supervised training process with manually labeled successful or failure results, our system can correctly estimate the resulting state of a manipulation activity. We present experiments on our bimanual manipulation demonstrator and evaluate the results.

2012 12th IEEE-RAS International Conference on Humanoid Robots (Humanoids 2012)

“…[8]. [7] includes knowledge about manipulation constraints during the planning step and tries to verify them afterwards. In [8] the symbolic output is mapped to a accessibility list calculated a priori, which handles all known geometric states for the corresponding actions.…”

Section: Related Workmentioning

confidence: 99%

Things are made for what they are: Solving manipulation tasks by using functional object classes

Leidner

Borst

Hirzinger

2012

Solving arbitrary manipulation tasks is a key feature for humanoid service robots. However, especially when tasks involve handling complex mechanisms or using tools, a generic action description is hard to define. Different objects require different handling methods. Therefore, we try to solve manipulation tasks from point of view of the object, rather than in the context of the robot. Action templates within the object context are introduced to resolve object specific task constraints. As part of a centralized world representation, the action templates are integrated into the planning process. This results in an intuitive way of solving manipulation tasks. The underlying architecture as well as the mechanisms are discussed within this paper. The proposed methods are evaluated in two experiments.