This paper presents a new neural networks-based method to solve the motion planning problem, i.e. to construct a collision-free path for a moving object among fixed obstacles. Our ‘navigator’ basically consists of two neural networks: The first one is a modified feed-forward neural network, which is used to determine the configuration space; the moving object is modelled as a configuration point in the configuration space. The second neural network is a modified bidirectional associative memory, which is used to find a path for the configuration point through the configuration space while avoiding the configuration obstacles. The basic processing unit of the neural networks may be constructed using logic gates, including AND gates, OR gates, NOT gate and flip flops. Examples of efficient solutions to difficult motion planning problems using our proposed techniques are presented.

A two-dimensional serial-driven manipulator is compared with two different parallel-driven manipulators, using workspace, power requirements and stiffness as criteria. The parallel-driven devices are based on the planar five-bar linkage; one has four revolute joints and one prismatic joint; the other has five revolute joints. Parallel operation is shown to offer advantages.

Computer simulation is a major tool in validation of robot motion planning systems, since, on the one hand, underlying theory of algorithms typically requires questionable assumptions and simplifications, and, on the other hand, experiments with hardware are necessarily limited by available resources and time. This is especially true when the motion planning system in question is based on sensor feedback and the generated trajectory is, therefore, unpredictable. This paper describes a simulation system ROPAS (for RObot PAth Simulation) for testing one approach — called Dynmic Path Planning (DPP) — to sensor-based robot collision avoidance in an environment with unknown obstacles. Using real time graphics animation of the motion planning system, the user can simulate the behavior of an autonomous vehicle or a robot arm manipulator with a fixed base. The overall structure of the system is described, and examples are presented.

A robotic manipulator is usually a very complicated system whose dynamics is too complicated time consuming for real-time control. The authors propose general criteria for designing an ideal robot whose dynamics is very much simpler than that of the conventional one. In this paper, dynamic characteristics of an ideally designed robot are investigated. The design guidelines were applied to a 6-degree-of-freedom PUMA 560 robot. Based upon the design concept dynamic equations of the redesigned robot were derived. Utilizing these equations, dynamic characteristics of the redesigned robot are investigated with respect to the computation efforts required, variation of the inertia matrix, joint input torque chracteristics, and couplings between the joints. A detailed comparison study is also made between the redesigned and conventional robots.

The problem of determining energy optimal walking motions for a bipedal walking robot is considered. A full dynamic model of a planar seven-link biped with feet is derived including the effects of impact of the feet with the ground. Motions of the hip and feet during a regular step are then modelled by 3rd order polynomials, the coefficients of which are obtained by numerically minimising an energy cost function. Results are given in the form of walking profiles and energy curves for the specific cases of motion over level ground, motion up and down an incline, and varying payload.