In this work we summarize the solution developed by Team KTH for the Amazon Picking Challenge 2016 in Leipzig, Germany. The competition simulated a warehouse automation scenario and it was divided in two tasks: a picking task where a robot picks items from a shelf and places them in a tote and a stowing task which is the inverse task where the robot picks items from a tote and places them in a shelf. We describe our approach to the problem starting from a high level overview of our system and later delving into details of our perception pipeline and our strategy for manipulation and grasping. The solution was implemented using a Baxter robot equipped with additional sensors.
In this chapter we summarize the solution developed by team KTH for the Amazon Picking Challenge 2016 in Leipzig, Germany. The competition, which simulated a warehouse automation scenario, was divided into two parts: a picking task, where the robot picks items from a shelf and places them into a tote, and a stowing task, where the robot picks items from a tote and places them in a shelf. We describe our approach to the problem starting with a high-level overview of the system, delving later into the details of our perception pipeline and strategy for manipulation and grasping. The hardware platform used in our solution consists of a Baxter robot equipped with multiple vision sensors.
Dual-arm manipulation tasks can be prescribed to a robotic system in terms of desired absolute and relative motion of the robot’s end-effectors. These can represent, e.g., jointly carrying a rigid object or performing an assembly task. When both types of motion are to be executed concurrently, the symmetric distribution of the relative motion between arms prevents task conflicts. Conversely, an asymmetric solution to the relative motion task will result in conflicts with the absolute task. In this work, we address the problem of designing a control law for the absolute motion task together with updating the distribution of the relative task among arms. Through a set of numerical results, we contrast our approach with the classical symmetric distribution of the relative motion task to illustrate the advantages of our method.
Coordinated dual-arm manipulation tasks can be broadly characterized as possessing absolute and relative motion components. Relative motion tasks, in particular, are inherently redundant in the way they can be distributed between end-effectors. In this work, we analyse cooperative manipulation in terms of the asymmetric resolution of relative motion tasks. We discuss how existing approaches enable the asymmetric execution of a relative motion task, and show how an asymmetric relative motion space can be defined. We leverage this result to propose an extended relative Jacobian to model the cooperative system, which allows a user to set a concrete degree of asymmetry in the task execution. This is achieved without the need for prescribing an absolute motion target. Instead, the absolute motion remains available as a functional redundancy to the system. We illustrate the properties of our proposed Jacobian through numerical simulations of a novel differential Inverse Kinematics algorithm.
In this work, we address the dual-arm manipula-tion of a two degrees-of-freedom articulated object that consistsof two rigid links. This can include a linkage constrainedalong two motion directions, or two objects in contact, wherethe contact imposes motion constraints. We formulate theproblem as a cooperative task, which allows the employment ofcoordinated task space frameworks, thus enabling redundancyexploitation by adjusting how the task is shared by the robotarms. In addition, we propose a method that can estimate thejoint location and the direction of the degrees-of-freedom, basedon the contact forces and the motion constraints imposed bythe object. Experimental results demonstrate the performanceof the system in its ability to estimate the two degrees of freedomindependently or simultaneously.
We propose a method that allows for dexterousmanipulation of an object by exploiting contact with an externalsurface. The technique requires a compliant grasp, enablingthe motion of the object in the robot hand while allowingfor significant contact forces to be present on the externalsurface. We show that under this type of grasp it is possibleto estimate and control the pose of the object with respect tothe surface, leveraging the trade-off between force control andmanipulative dexterity. The method is independent of the objectgeometry, relying only on the assumptions of type of grasp andthe existence of a contact with a known surface. Furthermore,by adapting the estimated grasp compliance, the method canhandle unmodelled effects. The approach is demonstrated andevaluated with experiments on object pose regulation andpivoting against a rigid surface, where a mechanical springprovides the required compliance.
We propose a method that allows for dexterous manipulation of an object by exploiting contact with an external surface. The technique requires a compliant grasp, enabling the motion of the object in the robot hand while allowing for significant contact forces to be present on the external surface. We show that under this type of grasp it is possible to estimate and control the pose of the object with respect to the surface, leveraging the trade-off between force control and manipulative dexterity. The method is independent of the object geometry, relying only on the assumptions of type of grasp and the existence of a contact with a known surface. Furthermore, by adapting the estimated grasp compliance, the method can handle unmodelled effects. The approach is demonstrated and evaluated with experiments on object pose regulation and pivoting against a rigid surface, where a mechanical spring provides the required compliance.
In this paper, we consider folding assembly as an assembly primitive suitable for dual-arm robotic assembly, that can be integrated in a higher level assembly strategy. The system composed by two pieces in contact is modelled as an articulated object, connected by a prismatic-revolute joint. Different grasping scenarios were considered in order to model the system, and a simple controller based on feedback linearisation is proposed, using force torque measurements to compute the contact point kinematics. The folding assembly controller has been experimentally tested with two sample parts, in order to showcase folding assembly as a viable assembly primitive.
In this poster the problem of bimanual robotic assembly is considered. In particular we introduce folding assembly which is an assembly task that requires significant rotational motion in order to mate two assembly pieces. We model the connection between the two parts as an ideal virtual prismatic and revolute joint while non-ideal effects on the part movements can be considered as special cases of the ideal virtual joint. The connection between the gripper and the assembly part is also studied by considering the case of rigid and non-rigid grasp. As a proof-of-concept, a stabilizing controller for the assembly task is derived following a bimanual master-slave approach under the assumption of rigid grasps. The controller is validated through simulation while an example object has been designed and printed for experimental validation of our assembly technique.
Robotic assembly in unstructured environments is a challenging task, due to the added uncertainties. These can be mitigated through the employment of assembly systems, which offer a modular approach to the assembly problem via the conjunction of primitives. In this paper, we use a dual-arm manipulator in order to execute a folding assembly primitive. When executing a folding primitive, two parts are brought into rigid contact and posteriorly translated and rotated. A switched controller is employed in order to ensure that the relative motion of the parts follows the desired model, while regulating the contact forces. The control is complemented with an estimator based on a Kalman filter, which tracks the contact point between parts based on force and torque measurements. Experimental results are provided, and the effectiveness of the control and contact point estimation is shown.
This study is concerned with the shared object manipulation problem in a physical Human-Robot Interaction (pHRI) setting. In such setups, the operator manipulates the object with the help of a robot. In this paper, the operator is assigned with the lead role, and the robot is passively following the forces/torques exerted by the operator. We propose a controller that is free from the well-known translation/rotation problem and enhances the operator's ability to move the object by reducing the human effort. The key point in our study is that the controller is defined based on the instantaneous center of rotation. The passivity of the system including the object and the manipulator has been evaluated. Simulation results validate the theoretical findings on different scenarios of subsequent rotations and translations of the object.
Dual-arm robots can overcome grasping force and payload limitations of a single arm by jointly grasping an object. However, if the distribution of mass of the grasped object is not even, each arm will experience different wrenches that can exceed its payload limits. In this work, we consider the problem of balancing the wrenches experienced by a dual-arm robot grasping a rigid tray. The distribution of wrenches among the robot arms changes due to objects being placed on the tray. We present an approach to reduce the wrench imbalance among arms through discrete bimanual manipulation. Our approach is based on sequential sliding motions of the grasp points on the surface of the object, to attain a more balanced configuration. We validate our modeling approach and system design through a set of robot experiments.
Dual-arm robots can overcome grasping force and payload limitations of a single arm by jointly grasping an object.However, if the distribution of mass of the grasped object is not even, each arm will experience different wrenches that can exceed its payload limits.In this work, we consider the problem of balancing the wrenches experienced by a dual-arm robot grasping a rigid tray.The distribution of wrenches among the robot arms changes due to objects being placed on the tray.We present an approach to reduce the wrench imbalance among arms through discrete bimanual manipulation.Our approach is based on sequential sliding motions of the grasp points on the surface of the object, to attain a more balanced configuration.%This is achieved in a discrete manner, one arm at a time, to minimize the potential for undesirable object motion during execution.We validate our modeling approach and system design through a set of robot experiments.
This paper refers to the problem of force regulation for a robot finger with soft tip in contact with a rigid surface with unknown geometrical characteristics. A simple adaptive controller is employed in order to cope with surface kinematic uncertainties and the asymptotic stability of the force error is shown for the spatial case. Simulation results demonstrate the controller performance.
This work deals with the problem of force regulation and position trajectory tracking for a robot in compliant contact under kinematic uncertainties. A robotic finger with a soft hemispherical tip of uncertain compliance is considered in contact with a rigid flat surface of unknown position and orientation. A novel adaptive controller is proposed and is proved to achieve the convergence of force and position errors to zero by identifying the slope given a persistently excited desired velocity. The performance of the proposed controller is demonstrated by a simulation example.
We consider the problem of force and position regulation for a robot finger with a soft tip in contact with a surface with unknown geometrical characteristics. An adaptive controller is proposed, and the asymptotic convergence of the applied force error and the estimated position error of the tip to zero is shown for the spatial case. Simulation results demonstrate the controller performance.
This work considers the problem of force/position regulationfor a robotic finger in compliant contact with an unknowncurved surface resulting in uncertain force and positioncontrol subspaces. The proposed controller is an adaptivecontrol scheme of a simple structure that achieves the desiredtarget by the on-line tuning of the position and force controlactions to their corresponding actual subspaces at the desiredpoint using motion state feedback. The local asymptoticstability of the system equilibrium point is proved and anestimate of the region of attraction is given. The controllerperformance is illustrated by a simulation example.
This work proposes a control law for the force position regulation problem under surface kinematic uncertainties. A compliant contact with friction is considered. The control law achieves exact regulation of force and position along the surface tangent by identifying the uncertain surface slope without any force, tactile and/or vision sensory requirements. The asymptotic stability of the closed loop system equilibrium point is proved in a local sense and is demonstrated by a simulation example.
The performance of a modified parallel control scheme is examined under surfacekinematic uncertainties using nonlinear stability analysis. The controlled system is a roboticfinger with a soft hemispherical fingertip of significant radius in contact with an unknownsurface. Analysis of the control system performance shows that force converges to the desiredvalue, whereas position errors stay close to zero and in some cases can even vanish despite uncertainties. Simulation results support the theoretical findings and illustrate the performance of theproposed controller.
This paper proposes a PID type regulator that achieves not only the global asymptotic convergence of the robot joint velocities and position errors to zero but it also guarantees a prescribed performance for the position error transient that is independent of system constants and control parameters. The proportional term of the control input uses a transformed error (TP) which incorporates the desired performance function; given sufficiently high proportional and damping gains, the proposed TPID controller ensures the position error's prescribed performance irrespective of constant disturbances and choice of control gains. Control parameter selection is merely confined in achieving admissible input torques. Simulation results for a three dof spatial robot confirm the theoretical analysis and illustrate the robustness of the prescribed performance regulator in case of time-variant bounded disturbances.
This work proposes a control law for the robot joint trajectory tracking in free space that achieves a prescribed performance of the joint position error under parametric uncertainties; the control law is extended for the case of bounded disturbances. A performance function incorporating predefined performance indices is used to produce a transformed error that is injected in the controller. Furthermore, asymptotic stability of the velocity error in case of zero disturbances and uniformly ultimate boundedness in an arbitrarily small region for bounded disturbances is achieved. Simulation results confirm the theoretical findings and compare the proposed controller with a conventional one.
This work proposes a distributed control scheme for the state agreement problem which can guarantee prescribed performance for the system transient. In particular, i) we consider a set of agents that can exchange information according to a static communication graph, ii) we a priori define time-dependent constraints at the edge's space (errors between agents that exchange information) and iii) we design a distributed controller to guarantee that the errors between the neighboring agents do not violate the constraints. Following this technique the contributions are twofold: a) the convergence rate of the system and the communication structure of the agents' network which are strictly connected can be decoupled, and b) the connectivity properties of the initially formed communication graph are rendered invariant by appropriately designing the prescribed performance bounds. It is also shown how the structure and the parameters of the prescribed performance controller can be chosen in case of connected tree graphs and connected graphs with cycles. Simulation results validate the theoretically proven findings while enlightening the merit of the proposed prescribed performance agreement protocol as compared to the linear one.
In robot constrained motion problems with frictional contacts, uncertainties on the contacted surface slope distort control targets and affect the control system performance. The surface normal direction cosines are in this case uncertain parameters that are involved in both the control law and the control targets. This work proposes an adaptive controller that achieves the desired goal given a persistently excited tip velocity magnitude on the surface by achieving the convergence of the estimated direction parameters to their actual values. The controller requires measurements of total force and joint variables. A simulation example for a 6 d.o.f. robot is used to illustrate the theoretical results.
In robot constrained motion problems on planar surfaces with frictional contacts, uncertainties on the contacted surface not only affect the control system performance but also distort control targets. The surface normal direction cosines are in this case uncertain parameters that are involved in both the control law and the control targets. This work proposes an adaptive learning controller that uses force and joint position/velocity measurements to simultaneously learn the surface orientation and achieve the desired goal. Simulation examples for a 6 dof robot are used to illustrate the theoretical results and the performance of the proposed controller in practical cases.
This work proposes an adaptive control law for the force position regulation problem under surface kinematic uncertainties. A compliant contact with friction is considered. The control law achieves exact regulation of force and position along the surface tangent by identifying the surface slope. The asymptotic stability of the closed loop system equilibrium point is proved in a local sense and is demonstrated by a simulation example
In robot contact tasks on planar surfaces with frictional contacts, kinematic uncertainties of thecontacted surface affect the control system performance and distort control targets. An adaptive controllerthat uses force and joint position/velocity measurements to simultaneously learn the surface orientation andachieve the desired goal is proposed. Simulation examples are used to illustrate the theoretical results andthe performance of the proposed controller in practical cases.
In this paper we are concerned with the problem of force and position regulation of a soft robotic finger in contact with a flat unknown surface. A type of parallel control scheme with gravity compensation is applied. Using nonlinear stability theory it is shown that the proposed controller achieves exact force regulation. It is further shown that position errors may stay close to zero and in some cases can even vanish even in the presence of uncertainties. Simulation results support theoretical findings.
This work deals with the problem of force/position trajectory tracking under uncertainties arising from surface position and orientation. A robotic finger with a soft hemispherical tip of uncertain compliance parameter is considered in contact with a rigid flat surface. A novel adaptive controller is designed using online estimates of the unknown parameters and is proved to achieve force and position tracking by ensuring the convergence of the estimated normal to the surface direction to its actual value. The performance of the proposed controller is demonstrated by a simulation example.
The problem of robot joint position control with prescribed performance guarantees is considered; the control objective is the error evolution within prescribed performance bounds in both problems of regulation and tracking. The proposed controllers do not utilize either the robot dynamic model or any approximation structures and are composed by simple PID or PD controllers enhanced by a proportional term of a transformed error through a transformation related gain. Under a sufficient condition for the damping gain, the proposed controllers are able to guarantee (i) predefined minimum speed of convergence, maximum steady state error and overshoot concerning the position error and (ii) uniformly ultimate boundedness (UUB) of the velocity error. The use of the integral term reduces residual errors allowing the proof of asymptotic convergence of both velocity and position errors to zero for the regulation problem under constant disturbances. Performance is a priori guaranteed irrespective of the selection of the control gain values. Simulation results of a three dof spatial robotic manipulator and experimental results of one dof manipulator are given to confirm the theoretical findings.
Fast and robust tracking against unknown disturbances is required in many modern complex robotic structures and applications, for which knowledge of the full exact nonlinear system is unreasonable to assume. This paper proposes a regressor-free nonlinear controller of low complexity which ensures prescribed performance position error tracking subject to unknown endogenous and exogenous bounded dynamics assuming that joint position and velocity measurements are available. It is theoretically shown and demonstrated by a simulation study that the proposed controller can guarantee tracking of the desired joint position trajectory with a priori determined accuracy, overshoot and speed of response. Preliminary experimental results to a simplified system are promising for validating the controller to more complex structures.
Fast and robust tracking against unknown disturbancesis required in many modern complex robotic structuresand applications for which knowledge of the full exact nonlinearsystem is unreasonable to assume. This paper proposesa regressor-free nonlinear controller of low complexity whichensures prescribed performance position error tracking subjectto unknown endogenous and exogenous bounded dynamicsassuming that joint position and velocity measurements areavailable. It is theoretically shown and demonstrated by asimulation study that the proposed controller can guaranteetracking of the desired joint position trajectory with a prioridetermined accuracy, overshoot and speed of response. Preliminaryexperimental results to a simplified system are promisingfor validating the controller to more complex structures.
This work refers to the problem of controlling robot motion and force in frictional contacts under environmental errors and particularly orientation errors that distort the desired control targets and control subspaces. The proposed method uses online estimates of the surface normal (tangent) direction to dynamically modify the control target and control space decomposition. It is proved that these estimates converge to the actual value even though the elasticity and friction parameters are unknown. The proposed control solution is demonstrated through simulation examples in three-dimensional robot motion tasks contacting both planar and curved surfaces.
The problem of robot force and position trajectory tracking is revisited in the case of an uncertain mapping of a surface into the robot space; then, although it is possible to define the desired trajectories with respect to the constraint surface, the lack of knowledge of the constraint direction in the robot space, means that the position and force control subspaces are uncertain. Such a case arises when for example the surface is misplaced. A novel adaptive controller is proposed using estimates of the constraint surface normal direction that converge to the actual value; the controller drives the actual force and position errors to zero given a persistently excited desired velocity on the surface. The performance of the proposed controller is demonstrated by a simulation example.
This work addresses the problem of joint position tracking with prescribed performance guarantees and proposes a novel controller able to guarantee i) predefined minimum speed of convergence, maximum steady state error and over shoot concerning the position tracking error and ii) uniformly ultimate boundedness of the system state. Neither the robot dynamic model nor any approximation structures are utilized in the control law. Control gain lower bounds are dependent on some prior robot knowledge but gain tuning is simplified since the only concern is to adopt those values that lead to reasonable input torques. Simulation results of a 3 dof spatial robotic manipulator are given to confirm the theoretical findings.
A control law achieving motion performance of quality and compliant reaction to unintended contacts for robot manipulators is proposed in this work. It achieves prescribed performance evolution of the position error under disturbance forces up to a tunable level of magnitude. Beyond this level, it deviates from the desired trajectory complying to what is now interpreted as unintentional contact force, thus achieving enhanced safety by decreasing interaction forces. The controller is a passivity model based controller utilizing an artificial potential that induces vanishing vector fields. Simulation results with a three degrees of freedom (DOF) robot under the control of the proposed scheme, verify theoretical findings and illustrate motion performance and compliance under an external force of short duration in comparison with a switched impedance scheme.
A control law combining motion performance quality and low stiffness reaction to unintended contacts is proposed in this work. It achieves prescribed performance evolution of the position error under disturbances up to a level related to model uncertainties and responds compliantly and with low stiffness to significant disturbances arising from impact forces. The controller employs a velocity reference signal in a model-based control law utilizing a non-linear time-dependent term, which embeds prescribed performance specifications and vanishes in case of significant disturbances. Simulation results with a three degrees of freedom (DOF) robot illustrate the motion performance and self-regulation of the output stiffness achieved by this controller under an external force, and highlights its advantages with respect to constant and switched impedance schemes. Experiments with a KUKA LWR 4+ demonstrate its performance under impact with a human while following a desired trajectory.
The problem of robot joint position and velocity tracking with prescribed performance guarantees is considered. The proposed controller is able to guarantee a prescribed transient and steady state behavior for the position and the velocity tracking errors without utilizing either the robot dynamic model or any approximation structures. Its performance is demonstrated and assessed via experiments with a KUKA LWR4+ arm.
In this work, we consider the force and position trajectory tracking for a robot manipulator in compliant contact with a surface in the presence of unknown stiffness and dynamic friction. A novel neuro-adaptive controller is proposed that exploits the approximation capabilities of the linear in the weights neural networks and the uniform ultimate boundedness of force and position error is proved. Simulation results illustrate the performance of the proposed controller.
In this work, the problem of force/position tracking for a robotic finger in compliant contact with a surface under non-parametric uncertainties is considered. In particular, structural uncertainties are assumed to characterize the compliance model as well as the robot dynamic model. A novel neuro-adaptive controller is proposed that exploits the approximation capabilities of the linear in the weights neural networks and the uniform ultimate boundedness of force and position error is proved. Simulation results illustrate the performance of the proposed controller
The problem of force/position tracking for a robotic manipulator in compliant contact with a surface under non-parametric uncertainties is considered. In particular, structural uncertainties are assumed to characterize the compliance and surface friction models, as well as the robot dynamic model. A novel neuro-adaptive controller is proposed, that exploits the approximation capabilities of the linear in the weights neural networks, guaranteeing the uniform ultimate boundedness of force and position error with respect to arbitrarily small sets, plus the boundedness of all signals in the closed loop. Simulations highlight the approach.
We study the problem of robot interaction with mechanisms that afford one degree of freedom motion, e.g., doors and drawers. We propose a methodology for simultaneous compliant interaction and estimation of constraints imposed by the joint. Our method requires no prior knowledge of the mechanisms' kinematics, including the type of joint, prismatic or revolute. The method consists of a velocity controller that relies on force/torque measurements and estimation of the motion direction, the distance, and the orientation of the rotational axis. It is suitable for velocity controlled manipulators with force/torque sensor capabilities at the end-effector. Forces and torques are regulated within given constraints, while the velocity controller ensures that the end-effector of the robot moves with a task-related desired velocity. We give proof that the estimates converge to the true values under valid assumptions on the grasp, and error bounds for setups with inaccuracies in control, measurements, or modeling. The method is evaluated in different scenarios involving opening a representative set of door and drawer mechanisms found in household environments.
In this paper we consider the problem of human-robot collaborative manipulation of an object, where the human is active in controlling the motion, and the robot is passively following the human's lead. Assuming that the human grasp of the object only allows for transfer of forces and not torques, there is a disambiguity as to whether the human desires translation or rotation. In this paper, we analyze different approaches to this problem both theoretically and in experiment. This leads to the proposal of a control methodology that uses switching between two different admittance control modes based on the magnitude of measured force to achieve disambiguation of the rotation/translation problem.
One of the big challenges for robots working outside of traditional industrial settings is the ability to robustly and flexibly grasp and manipulate tools for various tasks. When a tool is interacting with another object during task execution, several problems arise: a tool can be partially or completely occluded from the robot's view, it can slip or shift in the robot's hand - thus, the robot may lose the information about the exact position of the tool in the hand. Thus, there is a need for online calibration and/or recalibration of the tool. In this paper, we present a model-free online tool-tip calibration method that uses force/torque measurements and an adaptive estimation scheme to estimate the point of contact between a tool and the environment. An adaptive force control component guarantees that interaction forces are limited even before the contact point estimate has converged. We also show how to simultaneously estimate the location and normal direction of the surface being touched by the tool-tip as the contact point is estimated. The stability of the the overall scheme and the convergence of the estimated parameters are theoretically proven and the performance is evaluated in experiments on a real robot.
This paper introduces a method for estimating the constraints imposed by a human agent on a jointly manipulated object. These estimates can be used to infer knowledge of where the human is grasping an object, enabling the robot to plan trajectories for manipulating the object while subject to the constraints. We describe the method in detail, motivate its validity theoretically, and demonstrate its use in co-manipulation tasks with a real robot.
The problem of door opening is fundamental for household robotic applications. Domestic environments are generally less structured than industrial environments and thus several types of uncertainties associated with the dynamics and kinematics of a door must be dealt with to achieve successful opening. This paper proposes a method that can open doors without prior knowledge of the door kinematics. The proposed method can be implemented on a velocity-controlled manipulator with force sensing capabilities at the end-effector. The velocity reference is designed by using feedback of force measurements while constraint and motion directions are updated online based on adaptive estimates of the position of the door hinge. The online estimator is appropriately designed in order to identify the unknown directions. The proposed scheme has theoretically guaranteed performance which is further demonstrated in experiments on a real robot. Experimental results additionally show the robustness of the proposed method under disturbances introduced by the motion of the mobile platform.
This paper addresses the problem of robot interaction with objects attached to the environment through joints such as doors or drawers. We propose a methodology that requires no prior knowledge of the objects’ kinematics, including the type of joint - either prismatic or revolute. The method consists of a velocity controller which relies onforce/torque measurements and estimation of the motion direction,rotational axis and the distance from the center of rotation.The method is suitable for any velocity controlled manipulatorwith a force/torque sensor at the end-effector. The force/torquecontrol regulates the applied forces and torques within givenconstraints, while the velocity controller ensures that the endeffectormoves with a task-related desired tangential velocity. The paper also provides a proof that the estimates converge tothe actual values. The method is evaluated in different scenarios typically met in a household environment.
The problem of door opening is fundamental for robots operating in domestic environments. Since these environments are generally less structured than industrial environments, several types of uncertainties associated with the dynamics and kinematics of a door must be dealt with to achieve successful opening. This paper proposes a method that can open doors without prior knowledge of the door kinematics. The proposed method can be implemented on a velocity-controlled manipulator with force sensing capabilities at the end-effector. The method consists of a velocity controller which uses force measurements and estimates of the radial direction based on adaptive estimates of the position of the door hinge. The control action is decomposed into an estimated radial and tangential direction following the concept of hybrid force/motion control. A force controller acting within the velocity controller regulates the radial force to a desired small value while the velocity controller ensures that the end effector of the robot moves with a desired tangential velocity leading to task completion. This paper also provides a proof that the adaptive estimates of the radial direction converge to the actual radial vector. The performance of the control scheme is demonstrated in both simulation and on a real robot.
The problem of door opening is fundamental for robots operating in domesticenvironments. Since these environments are generally unstructured, a robot must deal withseveral types of uncertainties associated with the dynamics and kinematics of a door to achievesuccessful opening. The present paper proposes a dynamic force/velocity controller which usesadaptive estimation of the radial direction based on adaptive estimates of the door hinge’sposition. The control action is decomposed into estimated radial and tangential directions,which are proved to converge to the corresponding actual values. The force controller usesreactive compensation of the tangential forces and regulates the radial force to a desired smallvalue, while the velocity controller ensures that the robot’s end-effector moves with a desiredtangential velocity. The performance of the control scheme is demonstrated in simulation witha 2 DoF planar manipulator opening a door.