Advanced Robotics

Kondo, Koichi; Kimura, Fumihiko

doi: 10.1163/156855389X00073pmid: N/A

This paper describes a general and simple method for planning collision-free paths of manipulators. Many algorithms have been proposed for the collision avoidance problem, but no general and simple method has been developed which can be applied to any type of manipulator. The method based on the configuration space approach seems promising, but the configuration space is a multi-dimensional space and the amount of data concerning free space is enormous. However, most of these data are not used to plan a single motion of a manipulator. The free space concerned in planning a motion can be determined independently of the kinematic characteristics of the manipulator by a method based on grid expansion. The algorithm is as follows. First, collisions are detected during a linear movement in the configuration space and a set of collision-free configurations is calculated. Then the collision checking operations are propagated to neighbouring configurations. This process is continued until the wavefront from the initial configuration and that from the final configuration meet. This method has been implemented on a solid-model-based robot programming system and has been applied to an articulated manipulator.

Okano, Akira; Matsubara, Hitoshi; Inoue, Hirochika

doi: 10.1163/156855389X00082pmid: N/A

This paper describes a very high-level language processor for the block world, consisting of a task-oriented level and an object-oriented level. The command 'build arch' is taken as an example. First, the task-oriented-level processor translates the input (e.g. build arch) into an output description of the concrete goal state by referring to knowledge about the goal task in the concept model. The object-oriented-level processor then translates the description oT the goal state into the source code of the motion-level processor AL/L by automatically making task plans and computing the position and orientation of each object. If the concept of a goal task is pre-defined in the concept model, these processors can expand the goal task into the AL/L source code. As a result, human programmers do not need to consider the details of the environment or of the robot.

Noborio, Hiroshi; Fukuda, Shozo; Arimoto, Suguru

doi: 10.1163/156855389X00091pmid: N/A

The efficiency of off-line robot teaching with a graphics simulator depends on the speed of the interference check algorithm between the model of the robot and the model of its obstacles. This paper proposes an efficient algorithm whose computational complexity does not depend directly on the number of obstacles and the shape complexity of each obstacle. In this work, the octree representation is adopted as the model of the robot's environment. It registers all obstacles in the environment with a hierarchical structure in positioning. On the other hand, the boundary representation (B-Reps) is adopted as the robot model. It can represent easily a complex robot motion including rotation by updating its coordinates table every sampling interval. The algorithm consists of a basic process which assigns successively each patch of the B-Reps within a region to some of the eight subregions when the region is divided into them. Then the division is guided recursively by the hierarchical structure of the octree. With the aid of both information induced by the assignment for a region and spatial information inherent to the region in the octree, the algorithm can rapidly select only regions that intersect both the robot and its obstacles. From this selection, it follows that the interference check algorithm deals with only parts of obstacles which lie around the robot. As a result, the algorithm runs rapidly even in a cluttered environment. Finally, the computational complexity of the algorithm is evaluated, and the reasonableness of the evaluation and the efficiency of the algorithm are further ascertained by several experiments.

Kimura, Ichiro; Tadano, Jutaroh

doi: 10.1163/156855389X00109pmid: N/A

The needs, state-of-the-art, and future prospects of hospital robots are described. As an example, the development and details of guide and carry robots which have been developed for hospital use by Saga University and Saga Medical School are discussed. Some comments are also made on the conditions required for robots of this kind with regard to patients, their families, and hospital personnel.

Shioya, Akio; Sasama, Hiroshi

doi: 10.1163/156855389X00118pmid: N/A

Kawato, Mitsuo

doi: 10.1163/156855389X00127pmid: N/A

In order to control voluntary movements, the central nervous system must solve the following three computational problems at different levels: (1) the determination of a desired trajectory in visual coordinates; (2) the transformation of its coordinates into body coordinates; and (3) the generation of motor command. Concerning these problems, relevant experimental observations obtained in the field of neuroscience are briefly reviewed. On the basis of physiological information and previous models, we propose computational theories and a neural network model which account for these three problems. (1) A minimum torque-change model which predicts a wide range of trajectories in human multi-joint arm movements is proposed as a computational model for trajectory formation. (2) An iterative learning scheme is presented as an algorithm which solves the coordinate transformation and the control problem simultaneously. This algorithm can be regarded as a Newton-like method in function spaces. (3) A neural network model for generation of motor command is proposed. This model contains internal neural models of the motor system and its inverse system. The inverse-dynamics model is acquired by heterosynaptic plasticity using a feedback motor command (torque) as an error signal. The hierarchical arrangement of these neural networks and their global control are discussed. Their applications to robotics are also discussed.