A New Noise-Tolerant Obstacle Avoidance Scheme for Motion Planning of Redundant Robot Manipulators

Avoiding obstacle(s) is a challenging issue in the research of redundant robot manipulators. In addition, noise from truncation, rounding, and model uncertainty is an important factor that affects greatly the obstacle avoidance scheme. In this paper, based on the neural dynamics design formula, a new scheme with the pseudoinverse-type formulation is proposed for obstacle avoidance of redundant robot manipulators in a noisy environment. Such a scheme has the capability of suppressing constant and bounded time-varying noises, and it is thus termed as the noise-tolerant obstacle avoidance (NTOA) scheme in this paper. Theoretical results are also given to show the excellent property of the proposed NTOA scheme (particularly in noise situation). Based on a PA10 robot manipulator with point and window-shaped obstacles, computer simulation results are presented to further substantiate the efficacy and superiority of the proposed NTOA scheme for motion planning of redundant robot manipulators

A "Sidewinding" Locomotion Gait for Hyper-Redundant Robots

This paper considers the kinematics of a novel form of hyper-redundant mobile robot locomotion which is analogous to the 'sidewinding' locomotion of desert snakes. This form of locomotion can be generated by a repetitive travel wave of mechanism bending. Using a continuous backbone curve model, we develop algorithms which enable travel in a uniform direction as well as changes in direction

Simulated and experimental results of dual resolution sensor based planning for hyper-redundant manipulators

This paper presents a dual-resolution local sensor based planning method for hyper-redundant robot mechanisms. Two classes of sensor feedback control methods, working at different sampling rates and different spatial resolutions, are considered: full shape modification (FSM), and partial shape modification (PSM). FSM and PSM cooperate to utilize a mechanism's hyper-redundancy to enable both local obstacle avoidance and end-effector placement in real-time. These methods have been implemented on a thirty degree of freedom hyper-redundant manipulator which has 11 ultrasonic distance measurement sensors and 20 infrared proximity sensors. The implementation of these algorithms in a dual CPU real-time control computer, an innovative sensor bus architecture, and a novel graphical control interface are described. Experimental results obtained using this test bed show the efficacy of the proposed method

HARMONIOUS -- Human-like reactive motion control and multimodal perception for humanoid robots

For safe and effective operation of humanoid robots in human-populated environments, the problem of commanding a large number of Degrees of Freedom (DoF) while simultaneously considering dynamic obstacles and human proximity has still not been solved. We present a new reactive motion controller that commands two arms of a humanoid robot and three torso joints (17 DoF in total). We formulate a quadratic program that seeks joint velocity commands respecting multiple constraints while minimizing the magnitude of the velocities. We introduce a new unified treatment of obstacles that dynamically maps visual and proximity (pre-collision) and tactile (post-collision) obstacles as additional constraints to the motion controller, in a distributed fashion over surface of the upper-body of the iCub robot (with 2000 pressure-sensitive receptors). The bio-inspired controller: (i) produces human-like minimum jerk movement profiles; (ii) gives rise to a robot with whole-body visuo-tactile awareness, resembling peripersonal space representations. The controller was extensively experimentally validated, including a physical human-robot interaction scenario.Comment: 14 pages, 7 figure

Final Technical Report for DOE Grant DE-FG02-02ER83371, Phase II

The purpose of this research was to develop a telerobotic master device consisting of a 7-axis backdrivable robotic arm, and a pressure-sensitive grip-controller integrated with a Compact Remote Console (CRC), thus creating a highly functional teleoperation station targeted to control a 6-axis industrial robotic arm and dexterous robotic hand to be used for demolition work in a nuclear setting. We successfully completed the development of one of the world?s smallest brushless motor controllers due partially to funding through this grant. These controllers are used to drive the motors in the master robotic arm. We also completed the development of an improved model of a highly advanced 4 degree-of-freedom arm ? this same arm is the core component in the teleoperation system. The WAM arm and a 3-axis gimbals were integrated with a commercially available CRC at our consultant?s lab at University of Tennessee. Additional support hardware and software were combined to tie the master control system to an existing industrial robot in the lab. A master controller for a dexterous hand was developed and became an integral part of the gimbals handle. Control algorithms were developed and the software was written and implemented. The entire system was then debugged and tested. Results of the prototype system are promising. The WAM Arm, gimbals, hand controller and CRC were successful integrated. Testing of the system to control the 6-axis industrial arm and prototype dexterous hand showed great potential. Relatively simple tasks were successfully performed at slow speeds. Some of the testing was hampered by problems with the slave dexterous hand. This is a prototype hand being developed by Barrett under a different Phase II program. Potential improvements and advancements to the system include improving the control code, and integration of a 2nd master controller arm in order to drive a 2nd slave arm and hand. In summary, the device is a complex system with advanced features and could be used as a universal platform for efficient controlling of robotic arms performing remote tasks in unstructured and uncertain environments such as those prevalent in environmental clean up

Biologically-inspired Motion Control for Kinematic Redundancy Resolution and Self-sensing Exploitation for Energy Conservation in Electromagnetic Devices

This thesis investigates particular topics in advanced motion control of two distinct mechanical systems: human-like motion control of redundant robot manipulators and advanced sensing and control for energy-efficient operation of electromagnetic devices. Control of robot manipulators for human-like motions has been one of challenging topics in robot control for over half a century. The first part of this thesis considers methods that exploits robot manipulators’ degrees of freedom for such purposes. Jacobian transpose control law is investigated as one of the well-known controllers and sufficient conditions for its universal convergence are derived by using concepts of “stability on a manifold” and “transferability to a sub-manifold”. Firstly, a modification on this method is proposed to enhance the rectilinear trajectory of the robot end-effector. Secondly, an abridged Jacobian controller is proposed that exploits passive control of joints to reduce the attended degrees of freedom of the system. Finally, the application of minimally-attended controller for human-like motion is introduced. Electromagnetic (EM) access control systems are one of growing electronic systems which are used in applications where conventional mechanical locks may not guarantee the expected safety of the peripheral doors of buildings. In the second part of this thesis, an intelligent EM unit is introduced which recruits the selfsensing capability of the original EM block for detection purposes. The proposed EM device optimizes its energy consumption through a control strategy which regulates the supply to the system upon detection of any eminent disturbance. Therefore, it draws a very small current when the full power is not needed. The performance of the proposed control strategy was evaluated based on a standard safety requirement for EM locking mechanisms. For a particular EM model, the proposed method is verified to realize a 75% reduction in the power consumption

Collision-free path planning for robots using B-splines and simulated annealing

This thesis describes a technique to obtain an optimal collision-free path for an automated guided vehicle (AGV) and/or robot in two and three dimensions by synthesizing a B-spline curve under geometric and intrinsic constraints. The problem is formulated as a combinatorial optimization problem and solved by using simulated annealing. A two-link planar manipulator is included to show that the B-spline curve can also be synthesized by adding kinematic characteristics of the robot. A cost function, which includes obstacle proximity, excessive arc length, uneven parametric distribution and, possibly, link proximity costs, is developed for the simulated annealing algorithm. Three possible cases for the orientation of the moving object are explored: (a) fixed orientation, (b) orientation as another independent variable, and (c) orientation given by the slope of the curve. To demonstrate the robustness of the technique, several examples are presented. Objects are modeled as ellipsoid type shapes. The procedure to obtain the describing parameters of the ellipsoid is also presented