Advances in Motion Sensing and Control for Robotic Applications [electronic resource] : Selected Papers from the Symposium on Mechatronics, Robotics, and Control (SMRC’18)- CSME International Congress 2018, May 27-30, 2018 Toronto, Canada /
Janabi-Shariﬁ, Farrokh.editor.
Melek, William.editor.
This book reports on advances in sensing, modeling and control methods for different robotic platforms such as multi-degree of freedom robotic arms, unmanned aerial vehicles and autonomous mobile platforms. Based on 2018 Symposium on Mechatronics, Robotics, and Control (SMTRC’18), held as part of the 2018 CSME International Congress, in York University, Toronto, Canada, the book covers a variety of topics, from filtering and state estimation to adaptive control of reconfigurable robots and more. Next-generation systems with advanced control, planning, perception and interaction capabilities will achieve functionalities far beyond today’s technology. Two key challenges remaining for advanced robot technologies are related to sensing and control in robotic systems. Advanced perception is needed to navigate changing environments. Adaptive and intelligent control systems must be developed to enable operation in unstructured and dynamic environments. The selected chapters in this book focus on both of the aforementioned areas and highlight the main trends and challenges in robot sensing and control. The first part of the book introduces chapters which focus on advanced perception and sensing for robotics applications. They include sensor filtering and state estimation for bipedal robots and motion capture systems analysis. The second part focuses on different modeling and control methods for robotic systems including flight control for UAVs, multi-variable robust control for modular and reconfigurable robotics and control for precision micromanipulation.
Includes bibliographical references and index.
Sensor Filtering and State Estimation of a Fast Simulated Planar Bipedal Robot -- Comparative Analysis of OptiTrack Motion Capture Systems  -- Online Tuning Rule-Based Adaptive Speed Control Algorithm for DC Motors Using Recursive Least Squares with Forgetting -- Propeller Performance in Presence of Freestream: Applications in Modeling Multirotor UAVs -- Robust Cooperative Close Formation Flight Control of Multiple Unmanned Aerial Vehicles -- Dry Surface Micromanipulation Using an Untethered Magnetic Microrobot -- Sliding Mode Control Design of a Two-Wheel Inverted Pendulum Robot: Simulation, Design and Experiments -- Decentralized Model Reference Adaptive Control Design for Modular and Reconfigurable Robots. .
This book reports on advances in sensing, modeling and control methods for different robotic platforms such as multi-degree of freedom robotic arms, unmanned aerial vehicles and autonomous mobile platforms. Based on 2018 Symposium on Mechatronics, Robotics, and Control (SMTRC’18), held as part of the 2018 CSME International Congress, in York University, Toronto, Canada, the book covers a variety of topics, from filtering and state estimation to adaptive control of reconfigurable robots and more. Next-generation systems with advanced control, planning, perception and interaction capabilities will achieve functionalities far beyond today’s technology. Two key challenges remaining for advanced robot technologies are related to sensing and control in robotic systems. Advanced perception is needed to navigate changing environments. Adaptive and intelligent control systems must be developed to enable operation in unstructured and dynamic environments. The selected chapters in this book focus on both of the aforementioned areas and highlight the main trends and challenges in robot sensing and control. The first part of the book introduces chapters which focus on advanced perception and sensing for robotics applications. They include sensor filtering and state estimation for bipedal robots and motion capture systems analysis. The second part focuses on different modeling and control methods for robotic systems including flight control for UAVs, multi-variable robust control for modular and reconfigurable robotics and control for precision micromanipulation.
Control engineering.
Robotics.
Mechatronics.
Engineering design.
Artificial intelligence.
Control, Robotics, Mechatronics.
Engineering Design.
Artificial Intelligence.