Analytical Workspace, Kinematics, and Foot Force Based Stability of Hexapod Walking Robots

Many environments are inaccessible or hazardous for humans. Remaining debris after earthquake and fire, ship hulls, bridge installations, and oil rigs are some examples. For these environments, major effort is being placed into replacing humans with robots for manipulation purposes such as search and rescue, inspection, repair, and maintenance. Mobility, manipulability, and stability are the basic needs for a robot to traverse, maneuver, and manipulate in such irregular and highly obstructed terrain. Hexapod walking robots are as a salient solution because of their extra degrees of mobility, compared to mobile wheeled robots. However, it is essential for any multi-legged walking robot to maintain its stability over the terrain or under external stimuli. For manipulation purposes, the robot must also have a sufficient workspace to satisfy the required manipulability. Therefore, analysis of both workspace and stability becomes very important. An accurate and concise inverse kinematic solution for multi-legged robots is developed and validated. The closed-form solution of lateral and spatial reachable workspace of axially symmetric hexapod walking robots are derived and validated through simulation which aid in the design and optimization of the robot parameters and workspace. To control the stability of the robot, a novel stability margin based on the normal contact forces of the robot is developed and then modified to account for the geometrical and physical attributes of the robot. The margin and its modified version are validated by comparison with a widely known stability criterion through simulated and physical experiments. A control scheme is developed to integrate the workspace and stability of multi-legged walking robots resulting in a bio-inspired reactive control strategy which is validated experimentally

Automatic fine motor control behaviours for autonomous mobile agents operating on uneven terrains

A novel mechanism able to produce increasingly stable paths for mobile robotic agents travelling over uneven terrain is proposed in this paper. In doing so, cognitive agents can focus on higher-level goal planning, with the increased confidence the resulting tasks will be automatically accomplished via safe and reliable paths within the lower-level skills of the platform. The strategy proposes the extension of the Fast Marching level-set method of propagating interfaces in 3D lattices with a metric to reduce robot body instability. This is particularly relevant for kinematically reconfigurable platforms which significantly modify their mass distribution through posture adaptation, such as humanoids or mobile robots equipped with manipulator arms or varying traction arrangements. Simulation results of an existing reconfigurable mobile rescue robot operating on real scenarios illustrate the validity of the proposed strategy. Copyright 2010 ACM

Model-Based Stability Analysis for Mobile Manipulators

Analisi della stabilità del movimento di un sistema composto da piattaforma mobile, sulla quale è stato montato un robot a 6 assi rotazionali. Per questo si sono calcolate le reazioni vincolari alla base del manipolatore attraverso l'implementazione dell'algoritmo di Newton-Euler, ed è stato fatto un lavoro di parameter estimation per stimare i parametri dinamici del manipolatore. Successivamente è stato applicato l'algoritmo Moment-Height Stability Measur

Climbing and Walking Robots

With the advancement of technology, new exciting approaches enable us to render mobile robotic systems more versatile, robust and cost-efficient. Some researchers combine climbing and walking techniques with a modular approach, a reconfigurable approach, or a swarm approach to realize novel prototypes as flexible mobile robotic platforms featuring all necessary locomotion capabilities. The purpose of this book is to provide an overview of the latest wide-range achievements in climbing and walking robotic technology to researchers, scientists, and engineers throughout the world. Different aspects including control simulation, locomotion realization, methodology, and system integration are presented from the scientific and from the technical point of view. This book consists of two main parts, one dealing with walking robots, the second with climbing robots. The content is also grouped by theoretical research and applicative realization. Every chapter offers a considerable amount of interesting and useful information

Stability analysis of electrical powered wheelchair-mounted robotic-assisted transfer device

The ability of people with disabilities to live in their homes and communities with maximal independence often hinges, at least in part, on their ability to transfer or be transferred by an assistant. Because of limited resources and the expense of personal care, robotic transfer assistance devices will likely be in great demand. An easy-to-use system for assisting with transfers, attachable to electrical powered wheelchairs (EPWs) and readily transportable, could have a significant positive effect on the quality of life of people with disabilities. We investigated the stability of our newly developed Strong Arm, which is attached and integrated with an EPW to assist with transfers. The stability of the system was analyzed and verified by experiments applying different loads and using different system configurations. The model predicted the distributions of the system’s center of mass very well compared with the experimental results. When real transfers were conducted with 50 and 75 kg loads and an 83.25 kg dummy, the current Strong Arm could transfer all weights safely without tip-over. Our modeling accurately predicts the stability of the system and is suitable for developing better control algorithms to enhance the safety of the device

Contact aware robust semi-autonomous teleoperation of mobile manipulators

In the context of human-robot collaboration, cooperation and teaming, the use of mobile manipulators is widespread on applications involving unpredictable or hazardous environments for humans operators, like space operations, waste management and search and rescue on disaster scenarios. Applications where the manipulator's motion is controlled remotely by specialized operators. Teleoperation of manipulators is not a straightforward task, and in many practical cases represent a common source of failures. Common issues during the remote control of manipulators are: increasing control complexity with respect the mechanical degrees of freedom; inadequate or incomplete feedback to the user (i.e. limited visualization or knowledge of the environment); predefined motion directives may be incompatible with constraints or obstacles imposed by the environment. In the latter case, part of the manipulator may get trapped or blocked by some obstacle in the environment, failure that cannot be easily detected, isolated nor counteracted remotely. While control complexity can be reduced by the introduction of motion directives or by abstraction of the robot motion, the real-time constraint of the teleoperation task requires the transfer of the least possible amount of data over the system's network, thus limiting the number of physical sensors that can be used to model the environment. Therefore, it is of fundamental to define alternative perceptive strategies to accurately characterize different interaction with the environment without relying on specific sensory technologies. In this work, we present a novel approach for safe teleoperation, that takes advantage of model based proprioceptive measurement of the robot dynamics to robustly identify unexpected collisions or contact events with the environment. Each identified collision is translated on-the-fly into a set of local motion constraints, allowing the exploitation of the system redundancies for the computation of intelligent control laws for automatic reaction, without requiring human intervention and minimizing the disturbance of the task execution (or, equivalently, the operator efforts). More precisely, the described system consist in two different building blocks. The first, for detecting unexpected interactions with the environment (perceptive block). The second, for intelligent and autonomous reaction after the stimulus (control block). The perceptive block is responsible of the contact event identification. In short, the approach is based on the claim that a sensorless collision detection method for robot manipulators can be extended to the field of mobile manipulators, by embedding it within a statistical learning framework. The control deals with the intelligent and autonomous reaction after the contact or impact with the environment occurs, and consist on an motion abstraction controller with a prioritized set of constrains, where the highest priority correspond to the robot reconfiguration after a collision is detected; when all related dynamical effects have been compensated, the controller switch again to the basic control mode

Robot Manipulators

Robot manipulators are developing more in the direction of industrial robots than of human workers. Recently, the applications of robot manipulators are spreading their focus, for example Da Vinci as a medical robot, ASIMO as a humanoid robot and so on. There are many research topics within the field of robot manipulators, e.g. motion planning, cooperation with a human, and fusion with external sensors like vision, haptic and force, etc. Moreover, these include both technical problems in the industry and theoretical problems in the academic fields. This book is a collection of papers presenting the latest research issues from around the world

Probabilistic stable motion planning with stability uncertainty for articulated vehicles on challenging terrains

© 2015, Springer Science+Business Media New York. A probabilistic stable motion planning strategy applicable to reconfigurable robots is presented in this paper. The methodology derives a novel statistical stability criterion from the cumulative distribution of a tip-over metric. The measure is dynamically updated with imprecise terrain information, localization and robot kinematics to plan safety-constrained paths which simultaneously allow the widest possible visibility of the surroundings by simultaneously assuming highest feasible vantage robot configurations. The proposed probabilistic stability metric allows more conservative poses through areas with higher levels of uncertainty, while avoiding unnecessary caution in poses assumed at well-known terrain sections. The implementation with the well known grid based A* algorithm and also a sampling based RRT planner are presented. The validity of the proposed approach is evaluated with a multi-tracked robot fitted with a manipulator arm and a range camera using two challenging elevation terrains data sets: one obtained whilst operating the robot in a mock-up urban search and rescue arena, and the other from a publicly available dataset of a quasi-outdoor rover testing facility