A snake-based scheme for path planning and control with constraints by distributed visual sensors

YesThis paper proposes a robot navigation scheme using wireless visual sensors deployed in an environment. Different from the conventional autonomous robot approaches, the scheme intends to relieve massive on-board information processing required by a robot to its environment so that a robot or a vehicle with less intelligence can exhibit sophisticated mobility. A three-state snake mechanism is developed for coordinating a series of sensors to form a reference path. Wireless visual sensors communicate internal forces with each other along the reference snake for dynamic adjustment, react to repulsive forces from obstacles, and activate a state change in the snake body from a flexible state to a rigid or even to a broken state due to kinematic or environmental constraints. A control snake is further proposed as a tracker of the reference path, taking into account the robot’s non-holonomic constraint and limited steering power. A predictive control algorithm is developed to have an optimal velocity profile under robot dynamic constraints for the snake tracking. They together form a unified solution for robot navigation by distributed sensors to deal with the kinematic and dynamic constraints of a robot and to react to dynamic changes in advance. Simulations and experiments demonstrate the capability of a wireless sensor network to carry out low-level control activities for a vehicle.Royal Society, Natural Science Funding Council (China

Real-time trajectory generation for dynamic systems with nonholonomic constraints using Player/Stage and NTG.

This thesis will present various methods of trajectory generation for various types of mobile robots. Then it will progress to evaluating Robot Operating Systems (ROS’s) that can be used to control and simulate mobile robots, and it will explain why Player/Stage was chosen as the ROS for this thesis. It will then discuss Nonlinear Trajectory Generation as the main method for producing a path for mobile robots with dynamic and kinematic constraints. Finally, it will combine Player, Stage, and NTG into a system that produces a trajectory in real-time for a mobile robot and simulates a differential drive robot being driven from the initial state to the goal state in the presence of obstacles. Experiments will include the following: Blobfinding for physical and simulated camera systems, position control of physical and simulated differential drive robots, wall following using simulated range sensors, trajectory generation for omnidirectional and differential drive robots, and a combination of blobfinding, position control, and trajectory generation. Each experiment was a success, to varying degrees. The culmination of the thesis will present a real-time trajectory generation and position control method for a differential drive robot in the presence of obstacles

Coordinated Control of a Mobile Manipulator

In this technical report, we investigate modeling, control, and coordination of mobile manipulators. A mobile manipulator in this study consists of a robotic manipulator and a mobile platform, with the manipulator being mounted atop the mobile platform. A mobile manipulator combines the dextrous manipulation capability offered by fixed-base manipulators and the mobility offered by mobile platforms. While mobile manipulators offer a tremendous potential for flexible material handling and other tasks, at the same time they bring about a number of challenging issues rather than simply increasing the structural complexity. First, combining a manipulator and a platform creates redundancy. Second, a wheeled mobile platform is subject to nonholonomic constraints. Third, there exists dynamic interaction between the manipulator and the mobile platform. Fourth, manipulators and mobile platforms have different bandwidths. Mobile platforms typically have slower dynamic response than manipulators. The objective of the thesis is to develop control algorithms that effectively coordinate manipulation and mobility of mobile manipulators. We begin with deriving the motion equations of mobile manipulators. The derivation presented here makes use of the existing motion equations of manipulators and mobile platforms, and simply introduces the velocity and acceleration dependent terms that account for the dynamic interaction between manipulators and mobile platforms. Since nonholonomic constraints play a critical role in control of mobile manipulators, we then study the control properties of nonholonomic dynamic systems, including feedback linearization and internal dynamics. Based on the newly proposed concept of preferred operating region, we develop a set of coordination algorithms for mobile manipulators. While the manipulator performs manipulation tasks, the mobile platform is controlled to always bring the configuration of the manipulator into a preferred operating region. The control algorithms for two types of tasks - dragging motion and following motion - are discussed in detail. The effects of dynamic interaction are also investigated. To verify the efficacy of the coordination algorithms, we conduct numerical simulations with representative task trajectories. Additionally, the control algorithms for the dragging motion and following motion have been implemented on an experimental mobile manipulator. The results from the simulation and experiment are presented to support the proposed control algorithms