ChuXin Chen

A vision system for robotic inspection and manipulation

A model-based approach has been proposed to make object recognition computationally tractable. In this approach, models associated with objects expected to appear in the scene are recorded in the systems knowledge base. The system extracts various features from the input images using robust, low-level, general-purpose operators. Finally, matching is performed between the image-derived features and the scene domain models to recognize objects. Factors affecting the successful design and implementation of model-based vision systems include the ability to derive suitable object models, the nature of image features extracted by the operators, a computationally effective matching approach, knowledge representation schemes, and effective control mechanisms for guiding the systemss overall operation. The vision system they describe uses gray-scale images, which can successfully handle complex scenes with multiple object types.<<ETX>>

Simulation and animation of sensor-driven robots

Most simulation and animation systems utilized in robotics are concerned with simulation of the robot and its environment without simulation of sensors. These systems have difficulty in handling robots that utilize sensory feedback in their operation. In this paper, a new design of an environment for simulation, animation, and visualization of sensor-driven robots is presented. As sensor technology advances, increasing numbers of robots are equipped with various types of sophisticated sensors. The main goal of creating the visualization environment is to aid the automatic robot programming and off-line programming capabilities of sensor-driven robots. The software system will help the users visualize the motion and reaction of the sensor-driven robot under their control program. Therefore, the efficiency of the software development is increased, the reliability of the software and the operation safety of the robot are ensured, and the cost of new software development is reduced. Conventional computer-graphics-based robot simulation and animation software packages lack of capabilities for robot sensing simulation. This paper describes a system designed to overcome this deficiency.

Developing telerobotic systems using virtual reality concepts

The basic operational scenario for many application domains is to deploy nonhuman system components in the hazardous workspace and keep the human operator away from the hazardous but real work environment. The operator is an essential element of the integrated system and is provided with various powerful displays (for both visual and nonvisual information) for telepresence and interactive controls for teleoperation. Thus, the operator stationed in the safe and virtual work environment, is able to cooperate with the robotic system in accomplishing an assigned task. The team has been investigating various problems associated with the use of virtual-reality based concepts in robot control and system development for the past several years. Some of the main ideas which underlie the investigations are, multiple sensory based operation, transparency between real and virtual mode operation, integrating sensing and task planning in simulation, and reliance on extensive and systematic experimental evaluation. The systems developed are useful for both off-online and online operation.

Simulation and graphical interface for programming and visualization of sensor-based robot operation

The authors describe a simulation environment which can be of utility in the design, development, and operation of sensor-driven robotic systems. This environment incorporates the ability to simulate sensory inputs and their effects on the planning and control functions. A detailed design of the simulator is presented. The simulator is integrated within an entire robotic system, and is utilized for automatic robot programming. Alternatively, the simulated system operation flow can be controlled through either a teach mode or a program mode. Five sensing modalities can be simulated: proximity, point laser range, ultrasonic range, laser range depth imagery, and edge-based intensity imagery. The simulation and animation of a particular robot is described. The unique features of the simulator are that it simulates and utilizes sensory information feedback, it integrates planning and simulation, and it makes the switching between real and simulation mode in the robotic system transparent to the user.<<ETX>>

Sensor-Driven Intelligent Robotics

Publisher Summary Intelligent robotic systems should be capable of performing a range of complex tasks in unstructured and dynamic environments. This chapter discusses a number of important items associated with intelligent robots, role of vision sensing in intelligent robotics, and architecture for the design of an intelligent robot. The chapter also describes the computational task hierarchy that governs a model-based robot vision system, and presents a detailed tutorial on two important components of this hierarchy: image segmentation and matching. The main capabilities that intelligent robotic systems should possess include ability for perception of their environment, planning of their actions, and execution of the planned action. The two important components of a model-based vision system are image segmentation and the matching module. A procedure that allows transformation of 2D image coordinates into 3D world coordinates is also discussed in the chapter. The architecture and control aspects of an integrated sensor-based robotic system consist of six modules: supervisor, task planner, perception, motor, user interface, and knowledge-base. Intelligent, sensor-driven systems pose many challenging basic-research problems from a broad range of scientific and technological disciplines; however, there are many important application areas where such systems would be of significant value and utility, including hazardous environments such as nuclear plants, underwater, and space as well as many industrial-automation tasks. Recent advancements in the VLSI, computer-architectures, sensor-and robot-hardware, and artificial-intelligence fields may aid to the development of robust, practical, and cost-effective intelligent robotic systems for a wide variety of applications.

SAVIC: A SIMULATION, VISUALIZATION AND INTERACTIVE CONTROL ENVIRONMENT FOR MOBILE ROBOTS

A Simulation, Animation, Visualization and Interactive Control (SAVIC) environment has been developed for the design and operation of an integrated robotic manipulator system. This unique system possesses the abilities for (1) multi-sensor simulation, (2) kinematics and locomotion animation, (3) dynamic motion and manipulation animation, (4) transformation between real and virtual modes within the same graphics system, (5) ease in exchanging software modules and hardware devices between real and virtual world operations, and (6) interfacing with a real robotic system. This research is focused on enhancing the overall productivity of an integrated human-robot system. This paper describes a working system and illustrates the concepts by presenting the simulation, animation and control methodologies for a unique mobile robot with articulated tracks, a manipulator, and sensory modules.

Reactive locomotion control of articulated-tracked mobile robots for obstacle negotiation

This paper describes a reactive obstacle negotiating algorithm for articulated-tracked robots and demonstrates a working system by presenting the simulation, animation, and control methodologies for an articulated-tracked mobile robot with a manipulator and sensory modules. Developing the motion planning strategies for robots with articulated-tracked locomotin is much different from path planning techniques developed for wheeled robots traveling on a planar surface, as the problems are not limited to solving the obstacle avoidance only, but involve finding the obstacle negotiating strategy as well. The authors have been developing tracked mobile-manipulator systems for applications in hazardous environments. A simulation, animation, visualization and interactive control (SAVIC) environment has been developed for the design and operation of a integrated robotic manipulator system.

Transformation relationships for two commonly utilized Euler angle representations

Finding the transformation between different rotation representations in the development of high-level software systems that must be transported to different robots utilizing different rotation representation schemes is addressed. Euler angle representations, which are widely used in commercial robots and research laboratory robots, are considered. Typically, there are three different Euler angle representation systems, and each system describes a particular orientation of a rigid body in a reference coordinate frame by specifying three angles. Mathematical derivations of the transformation relationships underlying the parameters from two most commonly utilized representation schemes are presented. These relationships are derived in two different ways. One is based on the solution of the inverse transform for Euler angles and the other is based on the Napiers rules associated with spherical trigonometry. >

Object detection by step-wise analysis of spectral, spatial, and topographic features

Abstract In many computer vision systems accurate identification of various objects appearing in a scene is required. In this paper we address the problem of object detection in analyzing high resolution multispectral aerial images. Development of a practical object detection approach should consider issues of speed, accuracy, robustness, and amount of supervision allowed. The approach is based upon extraction of information from images and their systematic analysis utilizing available prior knowledge of various physical attributes of the objects. The step-wise approach examines spectral, spatial, and topographic features in making the object vs background decision. Techniques for the analysis of the spectral, spatial, and topographic features tend to be of increasing levels of computational complexity. The computationally simpler spectral feature analysis is performed for the entire image to detect candidate object regions. Only these regions are considered in the spatial feature analysis step to further reduce the number of candidate regions which need to be analyzed in the topographic feature analysis step. Such step-wise analysis makes the entire object detection process efficient by incorporating the process of “focus of attention” to identify regions of interest thus eliminating a relatively large portion of image from further detailed examination at every stage. Results of the experiments performed using several high resolution multispectral images have demonstrated the basic feasibility of the approach. The images utilized in the experiments are acquired from geographically different locations, at different times, with different types of background, and are of different resolution. Successful object detection with high accuracy and low false alarm rates indicate the robustness of this approach.

Novel graphical environment for virtual and real-world operations of tracked mobile manipulators

A simulation, animation, visualization and interactive control (SAVIC) environment has been developed for the design and operation of an integrated mobile manipulator system. This unique system possesses the abilities for (1) multi-sensor simulation, (2) kinematics and locomotion animation, (3) dynamic motion and manipulation animation, (4) transformation between real and virtual modes within the same graphics system, (5) ease in exchanging software modules and hardware devices between real and virtual world operations, and (6) interfacing with a real robotic system. This paper describes a working system and illustrates the concepts by presenting the simulation, animation and control methodologies for a unique mobile robot with articulated tracks, a manipulator, and sensory modules.