Challenges and Solutions for Autonomous Robotic Mobile Manipulation for Outdoor Sample Collection

In refinery, petrochemical, and chemical plants, process technicians collect uncontaminated samples to be analyzed in the quality control laboratory all time and all weather. This traditionally manual operation not only exposes the process technicians to hazardous chemicals, but also imposes an economical burden on the management. The recent development in mobile manipulation provides an opportunity to fully automate the operation of sample collection. This paper reviewed the various challenges in sample collection in terms of navigation of the mobile platform and manipulation of the robotic arm from four aspects, namely mobile robot positioning/attitude using global navigation satellite system (GNSS), vision-based navigation and visual servoing, robotic manipulation, mobile robot path planning and control. This paper further proposed solutions to these challenges and pointed the main direction of development in mobile manipulation

Fast Manipulability Maximization Using Continuous-Time Trajectory Optimization

A significant challenge in manipulation motion planning is to ensure agility in the face of unpredictable changes during task execution. This requires the identification and possible modification of suitable joint-space trajectories, since the joint velocities required to achieve a specific endeffector motion vary with manipulator configuration. For a given manipulator configuration, the joint space-to-task space velocity mapping is characterized by a quantity known as the manipulability index. In contrast to previous control-based approaches, we examine the maximization of manipulability during planning as a way of achieving adaptable and safe joint space-to-task space motion mappings in various scenarios. By representing the manipulator trajectory as a continuous-time Gaussian process (GP), we are able to leverage recent advances in trajectory optimization to maximize the manipulability index during trajectory generation. Moreover, the sparsity of our chosen representation reduces the typically large computational cost associated with maximizing manipulability when additional constraints exist. Results from simulation studies and experiments with a real manipulator demonstrate increases in manipulability, while maintaining smooth trajectories with more dexterous (and therefore more agile) arm configurations.Comment: In Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS'19), Macau, China, Nov. 4-8, 201

Advanced Strategies for Robot Manipulators

Amongst the robotic systems, robot manipulators have proven themselves to be of increasing importance and are widely adopted to substitute for human in repetitive and/or hazardous tasks. Modern manipulators are designed complicatedly and need to do more precise, crucial and critical tasks. So, the simple traditional control methods cannot be efficient, and advanced control strategies with considering special constraints are needed to establish. In spite of the fact that groundbreaking researches have been carried out in this realm until now, there are still many novel aspects which have to be explored

Support polygon in the hybrid legged-wheeled CENTAURO robot: modelling and control

Search for the robot capable to perform well in the real-world has sparked an interest in the hybrid locomotion systems. The hybrid legged-wheeled robots combine the advantages of the standard legged and wheeled platforms by switching between the quick and efficient wheeled motion on the flat grounds and the more versatile legged mobility on the unstructured terrains. With the locomotion flexibility offered by the hybrid mobility and appropriate control tools, these systems have high potential to excel in practical applications adapting effectively to real-world during locomanipuation operations. In contrary to their standard well-studied counterparts, kinematics of this newer type of robotic platforms has not been fully understood yet. This gap may lead to unexpected results when the standard locomotion methods are applied to hybrid legged-wheeled robots. To better understand mobility of the hybrid legged-wheeled robots, the model that describes the support polygon of a general hybrid legged-wheeled robot as a function of the wheel angular velocities without assumptions on the robot kinematics or wheel camber angle is proposed and analysed in this thesis. Based on the analysis of the developed support polygon model, a robust omnidirectional driving scheme has been designed. A continuous wheel motion is resolved through the Inverse Kinematics (IK) scheme, which generates robot motion compliant with the Non-Sliding Pure-Rolling (NSPR) condition. A higher-level scheme resolving a steering motion to comply with the non-holonomic constraint and to tackle the structural singularity is proposed. To improve the robot performance in presence to the unpredicted circumstances, the IK scheme has been enhanced with the introduction of a new reactive support polygon adaptation task. To this end, a novel quadratic programming task has been designed to push the system Support Polygon Vertices (SPVs) away from the robot Centre of Mass (CoM), while respecting the leg workspace limits. The proposed task has been expressed through the developed SPV model to account for the hardware limits. The omnidirectional driving and reactive control schemes have been verified in the simulation and hardware experiments. To that end, the simulator for the CENTAURO robot that models the actuation dynamics and the software framework for the locomotion research have been developed

Real-Time Trajectory Generation and Control of a Semi-Omnidirectional Mobile Robot

When controlling a wheeled mobile robot with four independently steerable driving wheels, the control of the wheel coordination must be handled. Both the direction and velocity of the wheels must be coordinated to allow for proper operation of the robot. The focus of this work is on the coordination of the wheel directions. Such coordination is mostly done by solving constraint equations of the system kinematics, but when the demands on the coordination are high, it is sometimes necessary to include the steering dynamics in the coordination control. With dynamics included the complexity of the wheel coordination increases, since constraints dependent on required angle changes and current velocities must be fulfilled. By calculating the dynamic limitations in each control cycle, the steering limit for the whole wheel base within the current control cycle can be found. With use of such wheel base limit, followable and coordinated wheel trajectories can be generated online. This thesis includes the construction of a dynamic model for inclusion of the steering dynamic limitations affecting the performance the most, the construction of the online trajectory generation idea, as well as implementation and validation on the real target wheeled mobile robot platform

Reuleaux: Robot Base Placement by Reachability Analysis

Before beginning any robot task, users must position the robot's base, a task that now depends entirely on user intuition. While slight perturbation is tolerable for robots with moveable bases, correcting the problem is imperative for fixed-base robots if some essential task sections are out of reach. For mobile manipulation robots, it is necessary to decide on a specific base position before beginning manipulation tasks. This paper presents Reuleaux, an open source library for robot reachability analyses and base placement. It reduces the amount of extra repositioning and removes the manual work of identifying potential base locations. Based on the reachability map, base placement locations of a whole robot or only the arm can be efficiently determined. This can be applied to both statically mounted robots, where position of the robot and work piece ensure the maximum amount of work performed, and to mobile robots, where the maximum amount of workable area can be reached. Solutions are not limited only to vertically constrained placement, since complicated robotics tasks require the base to be placed at unique poses based on task demand. All Reuleaux library methods were tested on different robots of different specifications and evaluated for tasks in simulation and real world environment. Evaluation results indicate that Reuleaux had significantly improved performance than prior existing methods in terms of time-efficiency and range of applicability.Comment: Submitted to International Conference of Robotic Computing 201