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In this chapter a novel approach to skill acquisition from human demonstration is presented. Usually the morphology of a robot manipulator is very different from the human arm and cannot simply copy a human motion. Instead the robot has to execute its own version of the skill demonstrated by the operator. Once a skill has been acquired by the robot it must also be able to generalize to other similar...
Grasp recognition is a major part of the approach for Programming-by-Demonstration (PbD) for five-fingered robotic hands. This chapter describes three different methods for grasp recognition for a human hand. A human operator wearing a data glove instructs the robot to perform different grasps. For a number of human grasps the finger joint angle trajectories are recorded and modeled by fuzzy clustering...
On many occasions, all the manipulators in the multi-manipulator system need to achieve the same joint configuration to fulfill certain coordination tasks. In this chapter, a distributed adaptive approach is proposed for solving this coordination problem based on the leader-follower strategy. The proposed algorithm is distributed because the controller for each follower manipulator is solely based...
An exemplar-based view-invariant human action recognition framework is proposed to recognize the human actions from any arbitrary viewpoint image sequence. In this framework, human action is modelled as a sequence of body key poses (i.e., exemplars) which are represented by a collection of silhouette images. The human actions are recognized by matching the observed image sequence to predefined exemplars,...
This research introduces and builds on the concept of Fuzzy Gaussian Inference (FGI) (Khoury and Liu in Proceedings of UKCI, 2008 and IEEE Workshop on Robotic Intelligence in Informationally Structured Space (RiiSS 2009), 2009) as a novel way to build Fuzzy Membership Functions that map to hidden Probability Distributions underlying human motions. This method is now combined with a Genetic Programming...
In this chapter we consider the detection of hazards within the ground plane immediately in front to a moving pedestrian. Consecutive views of the scene are acquired by a standard video camera. Using epipolar constraints between the two views, detected features are matched to compute the camera motion and reconstruct the 3-D geometry. Assuming the ground is planar, projective invariance of the cross-ratio...
A novel algorithm for camera calibration and correction is proposed in this chapter. A model of camera distortion is built without any prior knowledge. The calibration parameters are obtained by optimizing an objective function about the sum of the back projection errors using the LM algorithm. Also the distorted images are corrected by using the LM algorithm. A comparative study based on both synthetic...
While camera calibration is a fundamental yet challenging problem for 3D measurement, it has attracted intensive attention from 3D vision community. In this paper, we propose a new model to characterise camera distortion in the process of the camera calibration. This model attempts to blindly characterise the overall camera distortion without taking the specific radial, decentring, or thin prism distortion...
This chapter introduces a robot flocking system in which only minority members are the group leaders who have global trajectory knowledge, while majority members are the group followers who do not have global trajectory information, but can communicate with neighbors. The followers even do not know who the leaders are in the group. In order to keep the flocking group connected, all the group members...
Unmanned Aerial Vehicles (UAVs) is required to carry out duties such as surveillance, reconnaissance, search and rescue and security patrol missions. Autonomous operation of UAVs is a key to the success of these missions. In this chapter, we propose to use a behavior based control architecture to implement autonomous operation for UAV surveillance missions. This control architecture consists of two...
A new anti-disturbance control strategy is presented for a class of nonlinear robotic systems with multiple disturbances. This strategy is named hierarchical composite anti-disturbance control (HCADC). Two types of disturbances are studied. One is generated by an exogenous system with uncertainty and the other is described by an uncertain vector with the bounded H2 norm. The hierarchical...
Dynamic and complex indoor environments present a challenge for mobile robot navigation. The robot must be able to simultaneously map the environment, which often has repetitive features, whilst keep track of its pose and location. This chapter introduces some of the key considerations for human guided navigation. Rather than letting the robot explore the environment fully autonomously, we consider...
This chapter discusses the adaptation of perceptual modules of a partner robot based on classification and prediction through actual interactions with a human. The prediction is very important to extract the perceptual information for natural communication with a human. Therefore we proposed a prediction-based perceptual system composed of four layers: the input layer, clustering layer, prediction...
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