Titlebook: Robot Intelligence Technology and Applications 4; Results from the 4th Jong-Hwan Kim,Fakhri Karray,Hyun Myung Conference proceedings 2017 S

珠寶

灰姑娘

Android-Based Mobile Robotic Platform Performance Testing for Real-Time Navigationnes are also equipped with very powerful processors. Therefore a performance test of different devices with Android operating system including their sensorial equipment has been made to determine the usability of these devices for real-time robot navigation.

pacifist

Adaptive Control for Directional Drilling Systems with Delay and Parameter Uncertainty scenarios are conducted. The results show that both the controllers are able to stabilize the system in the presence of parameter uncertainties while maintaining the trajectory tracking error minimum.

做事過頭

Design and FPGA Implementation of a Fuzzy-PI Controller for Omnidirectional Robot Systemal of this work is the design of the Fuzzy-PI controller and the hardware implementation using FPGA resources. The controller can be implemented on an FPGA using software or hardware approach. For the latter approach, the Fuzzy-PI algorithm is implemented in VHDL language, synthesized, optimized, placed and routed, and downloaded on an FPGA board.

POINT

滴注

Trajectory Generation Using RNN with Context Information for Mobile Robots (HMM) and Support Vector Machine, but they are absent of continuity and inner state. In this paper, we tested several intelligent capabilities of the RNN, especially for memorization and generalization even under kidnapped situations, by simulating mobile robot in the experiments.

Nomadic

ROSLAM—A Faster Algorithm for Simultaneous Localization and Mapping (SLAM)ns SLAM (ROSLAM) which improves the runtime even further. We present an empirical evaluation of ROSLAM in a simulated environment which shows that it speeds up previous well known algorithms by 100?%.

不能強(qiáng)迫我

Adaptive Computation Algorithm for Simultaneous Localization and Mapping (SLAM)hances the localization and mapping accuracy along with better runtime performance. In an empirical evaluation in a rich environment, we show that ACSLAM runs about twice as fast as FastSLAM 2.0 and increases the accuracy of the location estimate by a factor of two.

圓錐

油膏