Robotics has achieved its greatest success to date in the world of industrial manufacturing.
Robot arms, or manipulators, comprise a 2 billion dollar industry. Bolted at its shoulder to
a specific position in the assembly line, the robot arm can move with great speed and accuracy
to perform repetitive tasks such as spot welding and painting (figure 1.1). In the electronics
industry, manipulators place surface-mounted components with superhuman
precision, making the portable telephone and laptop computer possible....
In this book, new results or developments from different research backgrounds and application fields are put together to provide a wide and useful viewpoint on these headed research problems mentioned above, focused on the motion planning problem of mobile ro-bots.
Recently, several solutions to the robot localisation problem have been proposed in the scientific
community. In this chapter we present a localisation of a visual guided quadruped
walking robot in a dynamic environment. We investigate the quality of robot localisation and
landmark detection, in which robots perform the RoboCup competition (Kitano et al., 1997).
The first part presents an algorithm to determine any entity of interest in a global reference
frame, where the robot needs to locate landmarks within its surroundings.
Today robots navigate autonomously in office environments as well as outdoors. They show their ability to beside mechanical and electronic barriers in building mobile platforms, perceiving the environment and deciding on how to act in a given situation are crucial problems. In this book we focused on these two areas of mobile robotics, Perception and Navigation.
Mobile robots navigation includes different interrelated activities: (i) perception, as obtaining and interpreting sensory information; (ii) exploration, as the strategy that guides the robot to select the next direction to go; (iii) mapping, involving the construction of a spatial representation by using the sensory information perceived; (iv) localization, as the strategy to estimate the robot position within the spatial map; (v) path planning, as the strategy to find a path towards a goal location being optimal or not; and (vi) path execution, where motor actions are determined and adapt...
Hội thảo toàn quốc về Điện tử - Truyền thông – An toàn thông tin, ATC/REV-2012
Multi-sensor mobile robot and the sensor fusion-based localization with Extended Kalman Filter
Trần Thuận Hoàng, Phùng Mạnh Dương, Đặng Anh Việt và Trần Quang Vinh Trường Đại học Công nghệ, Đại học Quốc gia Hà nội e-Mail: email@example.com.
Various methods for controlling mobile robot
systems have been developed which are generally classified into two categories: global planning and
local control. Many works, based on the complete
knowledge of the robot and the environment, use a
global planning method such as artificial potential
fields , connectivity graph, cell decomposition
, etc. These methods build some paths (set of
sub-goals) which are free of obstacles