Task-based compliance planning for multi-fingered robotic manipulations

Based on the analysis of the stiffness relation between the operational space and the fingertip space of multi-fingered hands, this paper provides a guideline of task-based compliance planning for multi-fingered robotic manipulations. In order to show the characteristics of the taskbased stiffness matrix, various two- and three-dimensional examples are illustrated. Also, it is shown that some of the coupling stiffness elements cannot be planned arbitrarily due to grasping geometry. Through the analytical results, it is concluded that the operational stiffness matrix should be carefully specified by considering the location of the compliance center and the grasp geometry of multifingered hands for successful grasping and manipulation tasks.     

Analogy between Juggling and Hopping: Active Object Manipulation Approach

Dynamic manipulation of an active object is introduced as a general model of hopping and juggling tasks. In this setting, juggling and hopping are two extreme cases of this general model. Behavioral resemblance of these two tasks is afterwards extended to a detailed mathematical analogy between them. Then the analogy is exploited to develop a unified and abstract planning framework for juggling and hopping. To this end, dynamic manipulation of an active object is decomposed into three distinct phases and two transitions: Carry I, Free flight and Carry II phases. These phases are analogous to Lift off, Free flight and Touch down in hopping. In the next step, a mathematical model for each phase is developed. It is shown that dynamic grasp (in Carry phases of juggling) and foot stability (in Support phases of hopping) conditions share similar sets of dynamic equations. Accordingly, Lift off/Release and Touch down/Catch conditions in hopping/juggling are derived. It is shown that analogous strategies can be developed for Lift off and Release. The analogy is held for Touch down and Catch conditions as well. It is discussed that in the planning framework the initial and the goal configurations of the three phases are set in a model-based and forward manner. To do so, Touch down/Landing time, Free flight duration and robot/object maneuvers during Free flight are used as free parameters for planning in order to ensure foot stability in hopping and dynamic grasp in juggling along with other constraints.     

A Framework for Automatic Generation of a Contact State Graph for Robotic Assembly

Dynamic manipulation of an active object is introduced as a general model of hopping and juggling tasks. In this setting, juggling and hopping are two extreme cases of this general model. Behavioral resemblance of these two tasks is afterwards extended to a detailed mathematical analogy between them. Then the analogy is exploited to develop a unified and abstract planning framework for juggling and hopping. To this end, dynamic manipulation of an active object is decomposed into three distinct phases and two transitions: Carry I, Free flight and Carry II phases. These phases are analogous to Lift off, Free flight and Touch down in hopping. In the next step, a mathematical model for each phase is developed. It is shown that dynamic grasp (in Carry phases of juggling) and foot stability (in Support phases of hopping) conditions share similar sets of dynamic equations. Accordingly, Lift off/Release and Touch down/Catch conditions in hopping/juggling are derived. It is shown that analogous strategies can be developed for Lift off and Release. The analogy is held for Touch down and Catch conditions as well. It is discussed that in the planning framework the initial and the goal configurations of the three phases are set in a model-based and forward manner. To do so, Touch down/Landing time, Free flight duration and robot/object maneuvers during Free flight are used as free parameters for planning in order to ensure foot stability in hopping and dynamic grasp in juggling along with other constraints.     

Translating Structured English to Robot Controllers

Recently, Linear Temporal Logic (LTL) has been successfully applied to high-level task and motion planning problems for mobile robots. One of the main attributes of LTL is its close relationship with fragments of natural language. In this paper, we take the first steps toward building a natural language interface for LTL planning methods with mobile robots as the application domain. For this purpose, we built a structured English language which maps directly to a fragment of LTL.     

Workspace Generation for Multifingered Manipulation

In this paper, we propose a novel numerical approach and algorithm to compute and visualize the workspace of a multifingered hand manipulating an object. Based on feasibility analysis of grasps, the proposed approach uses an optimization technique to first compute discretely the position boundary of the grasped object and then calculate the rotation ranges of the object at specified positions within the boundary. In other words, workspace generation with the approach is fulfilled by obtaining reachable boundaries of the grasped object in the sense of both position and orientation, and the discrete boundary points are computed by a series of optimization models. Unlike in workspace generation of other robotic systems where only geometric and kinematic parameters of the robots are considered, all factors including geometric, kinematic and force-related factors that affect the workspace of a hand–object system can be taken into account in our approach to generate the workspace of multifingered manipulation. Since various constraints can be integrated into the optimization models, our method is general and complete, with adaptability to various grasps and manipulations. Workspace generation with the approach in both planar and spatial cases are illustrated with examples. The approach provides an effective and general solution to the long-term open and challenging problem of workspace generation of multifingered manipulation. Part of the work has been published in the Proceedings of IEEE/RSJ IROS2008 and IEEE/ASME AIM2008.     

A General Framework for Planning Landmark-Based Motions for Mobile Robots

In this paper, we present a novel generic approach for planning landmark-based motion. The method consists in selecting automatically the most relevant landmarks along a preplanned geometric path. It proposes a strategy to correct the trajectory and to smoothly switch among the landmarks of the environment. Experimental results highlight the relevance of the proposed formalism.     

Planning and executing navigation among movable obstacles

This paper explores autonomous locomotion, reaching, grasping and manipulation for the domain of navigation among movable obstacles (NAMO). The robot perceives and constructs a model of an environment filled with various fixed and movable obstacles, and automatically plans a navigation strategy to reach a desired goal location. The planned strategy consists of a sequence of walking and compliant manipulation operations. It is executed by the robot with online feedback. We give an overview of our NAMO system, as well as provide details of the autonomous planning, online grasping and compliant hand positioning during dynamically stable walking. Finally, we present results of a successful implementation running on the humanoid robot HRP-2.     

Visibility-based probabilistic roadmaps for motion planning

This paper presents a variant of probabilistic roadmap methods (PRM) that recently appeared as a promising approach to motion planning. We exploit a free-space structuring of the configuration space into visibility domains in order to produce small roadmaps, called visibility roadmaps. Our algorithm integrates an original termination condition related to the volume of the free space covered by the roadmap. The planner has been implemented within a software platform allowing us to address a large class of mechanical systems. Experiments show the efficiency of the approach, in particular for capturing narrow passages of collision-free configuration spaces.     

Motion planning of manipulators regarding structural safety as a prior condition

In this paper, a motion-planning scheme that enables manipulators to avoid structural damage is described. Using this scheme, manipulators are encouraged to protect themselves from structural damage by searching for a safer attitude when their structural risk becomes high during their given tasks. The structural risk is determined by using two parameters, i.e., the resultant forces and total strain energy stored in the architecture, which are calculated by the finite element method. Three schemes of motion planning that use the structural parameters are compared by carrying out numerical tests with structurally severe tasks. Furthermore, the proposed strategy is implemented in the interface of a robotic arm to verify its validity. The experimental results revealed the practicability of the scheme in avoiding structural damage to the constituent members.     

Robot Motion Planning in Dynamic Uncertain Environments

In the real world, mobile robots often operate in dynamic and uncertain environments. Therefore, it is necessary to develop a motion planner capable of real-time planning that also addresses uncertainty concerns. In this paper, a new algorithm, Dynamic AO* (DAO*), is developed for navigation tasks of mobile robots. DAO* not only performs a good anytime behavior and offers a fast replanning framework, but also considers the motion uncertainty. Moreover, by incorporating DAO* with D* Lite, a new planning architecture, DDAO*, is represented to efficiently search in large state spaces. Finally, simulations and experiments are shown to verify the efficiency of the proposed algorithms.     

Motion order system for the end effector of an instrument used in endoscopic surgery

—Robotic operations of surgical instruments have greatly improved the workability of surgical operations. Even though they have high abilities, robotic surgery systems demand high cost and a large room space. As a solution to those problems, a number of instrument systems (Mid systems) have been proposed. Those systems are located at the middle position between conventional manual instrument systems and robotic surgery systems. This paper proposes some forceps that belong to the Mid systems. First, this paper discusses and sets up the conditions that should be considered when designing the Mid system instrument. This authors think it important to enable the forceps' jaws to rotate about its axis smoothly, to give the end effector with multi-d.o.f. motion (MDFM) the abilities of fine motion like that required for fine suturing work. Under the conditions of the Mid system, we discuss how we order the many motions of the instrument with MDFM by means of only one hand (Motion order). This paper tried forceps 'A' that has some electric switches for the Motion order for minimizing the end effector's tremble that may be transferred from the hand ordering the MDFM motions. The trial operations show that the fine touches of the switches cause little trembling on the end effector of forceps 'A'. However, they also show that it seems difficult for the end effector to take the required pose speedily. To respond to another demand that the end effector's pose has to change speedily, this paper proposes forceps 'B' that has a new mechanism that can give the pose of the end effector by taking the hand pose as the required one for the end effector separately from the jaws' rotational motion. The trial operations show that the new mechanism enables us to easily change the pose of the end effector. Even so, they also show that, in rapid pose change, the operator felt it difficult to follow the procedure after the pose change of the end effector. This paper clarifies, to a certain extent, the relationships of the Motion order method by the hand and the abilities of the end effector of the forceps.     

Whole Body Motion Noise Cancellation of a Robot for Improved Automatic Speech Recognition

The motors of a robot produce ego-motion noise that degrades the quality of recorded sounds. This paper describes an architecture that enhances the capability of a robot to perform automatic speech recognition (ASR) even as the entire body of the robot moves. The architecture consists of three blocks: (i) a multichannel noise reduction block, consisting of microphone-array-based sound localization, geometric source separation and post-filtering, (ii) a single-channel template subtraction block and (iii) an ASR block. As the first step of our analysis strategy, we divided the whole-body motion noise problem into three subdomains of arm, leg and head motion noise, according to their intensity levels and spatial location. Subsequently, by following a synthesis-by-analysis approach, we determined the best method for suppressing each type of ego-motion noise. Finally, we proposed to utilize a control module in our ASR framework; this module was designed to make decisions based on instantaneously detected motions, allowing it to switch to the most appropriate method for the current type of noise. This proposed system resulted in improvements of up to 50 points in word correct rates compared with results obtained by single microphone recognition of arm, leg and head motions.     

Pose Planning for a Mobile Manipulator Based on Joint Motions for Posture Adjustment to End-Effector Error

This paper proposes a motion planning method for a mobile manipulator. In general, humans can grasp an object by various ways which depend on object posture, position and so on. The objective of this paper is to present how to detect the pose of a mobile manipulator under the condition that several ways of grasping are given to the robot. Motion errors and object position errors are considered to detect robot pose in our method because these affect the grasp motion of the robot hand. Coping with these errors, we will propose an effective pose searching method for a mobile manipulator from numerous pose candidates. The performance of the proposed method is illustrated by simulation and experiment.     

约束环境中多指手操作的鲁棒控制

针对约束环境中的多指手操作系统,在考虑其动态模型的不确定性以及存在外界干扰的情况下,提出了一种鲁棒操作算法.对于模型的不确定性,该算法能够保证物体的位置误差、速度误差以及与环境之间的作用力误差具有全局指数收敛的特性.在存在外界干扰的情况下,系统满足给定的干扰抑制性能指标.同时,通过对多指手操作系统的内力进行鲁棒优化,进一步增强了系统的鲁棒干扰抑制性能.     

On Climbing Winding Stairs in an Open Mode for a New Robotic Wheelchair

This paper presents the mechanical design, locomotion and associated dynamic models of a new robotic wheelchair on climbing winding stairs. The prototype stair-climbing robotic wheelchair is constructed comprising a pair of rotational multi-limbed structures pivotally mounted on opposite sides of a support base so that the robotic wheelchair can ascend and descend stairs; in particular, the capability of climbing winding stairs is addressed. Based on the skid-steering analysis, the dynamic models for climbing winding stairs are developed for the trajectory planning and motion analyses. These models are required to ensure a passenger's safety in such a way that the robotic wheelchair is operated in an open mode. Moreover, an equivalent constraint method is proposed for the prescribed motion of the robotic wheelchair on climbing winding stairs. The results of the simulation and maneuver are reported that show the behavior of the prototype as it climbs winding stairs in a dynamic turning.     

基于神经符号的动力电池拆解任务与运动规划

建立完善的动力电池回收利用体系是我国新能源汽车高质量发展需要突破的瓶颈问题之一,研究和发展智能化、柔性化、精细化的高效拆解技术是其中的重要环节.但由于受非结构化的拆解环境和拆解过程中的不确定性等因素的影响,目前,动力电池拆解还采用人工为主、机器辅助拆解的方式,不仅低效,而且致使工作人员暴露在危险的工作环境中,亟需向自动化、智能化方式转变.研究基于神经符号理论对动态环境中动力电池的拆解任务进行研究,设计并实现了一套任务和运动规划系统.与现有的动力电池拆解系统相比,系统在自主性、可扩展性、可解释性、可学习性4方面具备明显的优势,这4方面的优势相辅相成,可以不断促进系统的完善和提高,为实现动力电池的智能化拆解铺平了道路.基于该系统实现了在复杂多变的拆解工作环境中动力电池连接约束件的智能拆解,验证了系统的可行性.     

Shape Control of a Hyper-Redundant Arm for Planar Object Manipulation

This paper discusses a method for controlling a hyper-redundant arm to manipulate an object on a plane. The hyper-redundant arm can perform simple whole-arm manipulation by coiling or wrapping around the object and then pulling the object toward the goal position. The process of object manipulation can be separated into two steps: encircling the object and transporting the object. In the process of encircling the object, the arm is controlled by a set of virtual constraints that guide the arm to reach around the object and encircle it, keeping the arm within a specified bound to ensure the circular shape around the object. In the process of transporting the object, a simplified desired shape is generated from a Bézier curve according to a given goal position and the arm geometry. Then, the gradient descent method is used to update the joint angles of the arm at each step to move the arm toward the desired shape until the object reaches its target position. The proposed method has been tested in both simulation and real experiments.     

Motion Planning Strategy for Finding an Object with a Mobile Manipulator in Three-Dimensional Environments

In this paper, we investigate the problem of minimizing the average time required to find an object in a known three-dimensional environment. We consider a 7-d.o.f. mobile manipulator with an 'eye-in-hand' sensor. In particular, we address the problem of searching for an object whose unknown location is characterized by a known probability density function. We present a discrete formulation, in which we use a visibility-based decomposition of the environment. We introduce a sample-based convex cover to estimate the size and shape of visibility regions in three dimensions. The resulting convex regions are exploited to generate trajectories that make a compromise between moving the manipulator base and moving the robotic arm. We also propose a practical method to approximate the visibility region in three dimensions of a sensor limited in both range and field of view. The quality and success of the generated paths depend significantly on the sensing robot capabilities. In this paper, we generate searching plans for a mobile manipulator equipped with a sensor limited in both field of view and range. We have implemented the algorithm and present simulation results.     

Sit-to-Stand and Stand-to-Sit Transfer Support for Complete Paraplegic Patients with Robot Suit HAL

Physical support of lower limbs during sit-to-stand and stand-to-sit transfers is important for an independent life of paraplegic patients. The purpose of this study is, therefore, to realize the control method of complete paraplegic patients during sit-to-stand and stand-to-sit transfers by using a 'robot suit HAL'. It is the most challenging issue because the HAL should start supporting the wearer's motions synchronizing his/her intention. Our proposed algorithm infers the intention based on a preliminary motion that is observed just before a desired motion so the patient could start the sit-to-stand or stand-to-sit transfers without any operation. When the HAL detects the intention to stand up and sit down, the HAL starts to support the wearer's weight and to control their body posture for stability during their transfer. The proposed algorithms embedded in the HAL were applied to a complete spinal cord injury patient in a clinical trial to confirm the effectiveness. The experimental results indicate that the proposed algorithms could support his sit-to-stand and stand-to-sit transfers safely and conveniently by keeping his stability and by reflecting his intentions. Consequently, we confirmed that the proposed method successfully supported the sit-to-stand and stand-to-sit transfers of the complete paraplegic patient with the HAL.