A Structured Prediction Approach for Robot Imitation Learning

We propose a structured prediction approach for robot imitation learning from demonstrations. Among various tools for robot imitation learning, supervised learning has been observed to have a prominent role. Structured prediction is a form of supervised learning that enables learning models to operate on output spaces with complex structures. Through the lens of structured prediction, we show how robots can learn to imitate trajectories belonging to not only Euclidean spaces but also Riemannian manifolds. Exploiting ideas from information theory, we propose a class of loss functions based on the f-divergence to measure the information loss between the demonstrated and reproduced probabilistic trajectories. Different types of f-divergence will result in different policies, which we call imitation modes. Furthermore, our approach enables the incorporation of spatial and temporal trajectory modulation, which is necessary for robots to be adaptive to the change in working conditions. We benchmark our algorithm against state-of-the-art methods in terms of trajectory reproduction and adaptation. The quantitative evaluation shows that our approach outperforms other algorithms regarding both accuracy and efficiency. We also report real-world experimental results on learning manifold trajectories in a polishing task with a KUKA LWR robot arm, illustrating the effectiveness of our algorithmic framework

A structured prediction approach for robot imitation learning

We propose a structured prediction approach for robot imitation learning from demonstrations. Among various tools for robot imitation learning, supervised learning has been observed to have a prominent role. Structured prediction is a form of supervised learning that enables learning models to operate on output spaces with complex structures. Through the lens of structured prediction, we show how robots can learn to imitate trajectories belonging to not only Euclidean spaces but also Riemannian manifolds. Exploiting ideas from information theory, we propose a class of loss functions based on the f-divergence to measure the information loss between the demonstrated and reproduced probabilistic trajectories. Different types of f-divergence will result in different policies, which we call imitation modes. Furthermore, our approach enables the incorporation of spatial and temporal trajectory modulation, which is necessary for robots to be adaptive to the change in working conditions. We benchmark our algorithm against state-of-the-art methods in terms of trajectory reproduction and adaptation. The quantitative evaluation shows that our approach outperforms other algorithms regarding both accuracy and efficiency. We also report real-world experimental results on learning manifold trajectories in a polishing task with a KUKA LWR robot arm, illustrating the effectiveness of our algorithmic framework

Constrained DMPs for Feasible Skill Learning on Humanoid Robots

In the context of humanoid skill learning, movement primitives have gained much attention because of their compact representation and convenient combination with a myriad of optimization approaches. Among them, a well-known scheme is to use Dynamic Movement Primitives (DMPs) with reinforcement learning (RL) algorithms. While various remarkable results have been reported, skill learning with physical constraints has not been sufficiently investigated. For example, when RL is employed to optimize the robot joint trajectories, the exploration noise could drive the resulting trajectory out of the joint limits. In this paper, we focus on robot skill learning characterized by joint limit avoidance, by introducing the novel Constrained Dynamic Movement Primitives (CDMPs). By controlling a set of transformed states (called exogenous states) instead of the original DMPs states, CDMPs are capable of maintaining the joint trajectories within the safety limits. We validate CDMPs on the humanoid robot iCub, showing the applicability of our approach

PSO-Based Optimal Coverage Path Planning for Surface Defect Inspection of 3C Components with a Robotic Line Scanner

The automatic inspection of surface defects is an important task for quality control in the computers, communications, and consumer electronics (3C) industry. Conventional devices for defect inspection (viz. line-scan sensors) have a limited field of view, thus, a robot-aided defect inspection system needs to scan the object from multiple viewpoints. Optimally selecting the robot's viewpoints and planning a path is regarded as coverage path planning (CPP), a problem that enables inspecting the object's complete surface while reducing the scanning time and avoiding misdetection of defects. However, the development of CPP strategies for robotic line scanners has not been sufficiently studied by researchers. To fill this gap in the literature, in this paper, we present a new approach for robotic line scanners to detect surface defects of 3C free-form objects automatically. Our proposed solution consists of generating a local path by a new hybrid region segmentation method and an adaptive planning algorithm to ensure the coverage of the complete object surface. An optimization method for the global path sequence is developed to maximize the scanning efficiency. To verify our proposed methodology, we conduct detailed simulation-based and experimental studies on various free-form workpieces, and compare its performance with a state-of-the-art solution. The reported results demonstrate the feasibility and effectiveness of our approach

Control strategy investigation for a down-scaledforwarder : Refinement, Testing nad Analysis

The predominant method of trees harvesting in Nordic countries is cut-to-length logging (CTL). CTL is realized by two machines: a harvester which is used for felling the trees, and a forwarder which is used for transporting the logs to a road accessible by trucks. To increase the productivity, one possible solution is to increase the forwarder driving speed. However, this will make the operator exposed to larger vibration and cause bigger tire-ground pressure. To solve the abovementioned problems, Skogforsk developed a six-wheel pendulum arm suspended forwarder with each wheel of the forwarder controlled individually by the corresponding hydraulic motor. Given that conducting the field tests on the real forwarder will be time consuming and inconvenient, a 1:5 down-scaled forwarder was manufactured previously to facilitate the research. Due to the size limitation, the hydraulic motors are replaced with the linear actuators besides a few other design changes. The work of this thesis is to further refine the down-scaled forwarder with the focus on implementing the control system. The forwarder is modeled using Simscape MultibodyTM which provides a 3D animation modelling environment. The control strategy is proposed in a perspective of kinematic control. The proposed control algorithm can balance the down-scaled forwarder orientation by solving a linear optimization problem in real time. Restricted by the sensors implementation and filter algorithms, only a simplified kinematics control is tested in the simulation and the real down-scaled forwarder. It can be seen in simulation that both the pitch and roll angle can be reduced greatly by driving through the Skoforsk standard test track with the simplified control method. Stability analysis method for the down-scaled forwarder is also discussed in this thesis. The main contribution of this thesis will be indicating a different point of view from the previous work in terms of control strategy proposal.Den dominerande metoden för att skörda träd i Norden är kortvirkesmetoden. Kortvirkesmetoden realiseras av två maskiner: en skördare som används för avverkning av träden och en forwarder som används för att transportera stockarna till en väg som är tillgänglig för lastbilar. För att öka produktiviteten är en möjlig lösning att öka forwarderns körhastighet. Detta kommer dock att bidrar till att operatören utsätts för större vibration och att marken utsätts för större däcktryck. För att lösa ovanstående problem har en sexhjulig forwarder med hjulupphängning i pendelarmar tidigare utvecklats där varje hjul styrs individuellt av en motsvarande hydraulmotor. Med tanke på att genomförande av fälttester på den verkliga forwardern skulle bli tids- och resurskrävande, har tidigare en 1: 5 nedskalad forwarder tillverkats för att underlätta forskningen. På grund av storleksbegränsningarna ersattes de hydrauliska motorerna med linjära cylindrar samt gjordes en del andra konstruktionsändringar. Arbetet med denna avhandling är att ytterligare förfina den nedskalade forwardern med fokus på att implementera styrsystemet. Forwardern är modellerad med Simscape Multibody TM som ger en 3D modellerings- och animeringsmiljö. Styrstrategin som föreslås är baserad på kinematik. Den föreslagna regleralgoritmen kan balansera den simulerade nedskalade forwardern genom att lösa ett linjärt optimeringsproblem i realtid. Begränsad av sensorprestanda och filteralgoritmer testas endast en förenklad kinematikreglering i simuleringen och i den verkliga nerskalade forwardern. Det kan ses i simulering att både pitch- och roll-vinklar kan minskas kraftigt även med den förenklade reglermetoden vid körning genom Skogforsks standardprovbana. Stabilitetsanalysmetoden för den nedskalade forwardern diskuteras också i denna avhandling. Huvudbidraget från detta examensarbets består i att en annan synvinkel presenterats jämfört med föregående arbeten när det gäller förslag till nya fungerande styrstrategier

A Structured Prediction Approach to Robot Imitation Learning

This thesis is primarily focused on movement primitives-based imitation learn- ing, within the context of robot programming by demonstration. Specifically, the imitation problem is tackled from a supervised-learning perspective. Therefore, it allows us to resort to theoretical tools from structured prediction, which can handle data-sets with complex structures. The first part of the thesis provides an overall background, in which we overview state-of-the-art imitation learning algorithms as well as discuss relevant technical tools. We formally introduce our contribution in part II. Our algorithm is not only capable of learning usual Euclidean trajectories (Chapter 7), but also trajectories lying on some manifold (Chapter 8). The capability of adapting manifold trajectories distinguishes our approach from other imitation learning algorithms. Subsequently, we provide a few extensions to augment our approach, including trajectory refinement by policy search (Chapter 10), imitation learning with constraints (Chapter 11), and probabilistic trajectory transfer (Chapter 12). We then conclude the thesis in the epilogue

Control Strategy Investigation for a Down-Scaled Forwarder : Refinement, Testing and Analysis

The predominant method of trees harvesting in Nordic countries is cut-to-length logging (CTL). CTL is realized by two machines: a harvester which is used for felling the trees, and a forwarder which is used for transporting the logs to a road accessible by trucks. To increase the productivity, one possible solution is to increase the forwarder driving speed. However, this will make the operator exposed to larger vibration and cause bigger tire-ground pressure. To solve the abovementioned problems, Skogforsk developed a six-wheel pendulum arm suspended forwarder with each wheel of the forwarder controlled individually by the corresponding hydraulic motor. Given that conducting the field tests on the real forwarder will be time consuming and inconvenient, a 1:5 down-scaled forwarder was manufactured previously to facilitate the research. Due to the size limitation, the hydraulic motors are replaced with the linear actuators besides a few other design changes. The work of this thesis is to further refine the down-scaled forwarder with the focus on implementing the control system. The forwarder is modeled using Simscape MultibodyTM which provides a 3D animation modelling environment. The control strategy is proposed in a perspective of kinematic control. The proposed control algorithm can balance the down-scaled forwarder orientation by solving a linear optimization problem in real time. Restricted by the sensors implementation and filter algorithms, only a simplified kinematics control is tested in the simulation and the real down-scaled forwarder. It can be seen in simulation that both the pitch and roll angle can be reduced greatly by driving through the Skoforsk standard test track with the simplified control method. Stability analysis method for the down-scaled forwarder is also discussed in this thesis. The main contribution of this thesis will be indicating a different point of view from the previous work in terms of control strategy proposal.Den dominerande metoden för att skörda träd i Norden är kortvirkesmetoden. Kortvirkesmetoden realiseras av två maskiner: en skördare som används för avverkning av träden och en forwarder som används för att transportera stockarna till en väg som är tillgänglig för lastbilar. För att öka produktiviteten är en möjlig lösning att öka forwarderns körhastighet. Detta kommer dock att bidrar till att operatören utsätts för större vibration och att marken utsätts för större däcktryck. För att lösa ovanstående problem har en sexhjulig forwarder med hjulupphängning i pendelarmar tidigare utvecklats där varje hjul styrs individuellt av en motsvarande hydraulmotor. Med tanke på att genomförande av fälttester på den verkliga forwardern skulle bli tids- och resurskrävande, har tidigare en 1: 5 nedskalad forwarder tillverkats för att underlätta forskningen. På grund av storleksbegränsningarna ersattes de hydrauliska motorerna med linjära cylindrar samt gjordes en del andra konstruktionsändringar. Arbetet med denna avhandling är att ytterligare förfina den nedskalade forwardern med fokus på att implementera styrsystemet. Forwardern är modellerad med Simscape Multibody TM som ger en 3D modellerings- och animeringsmiljö. Styrstrategin som föreslås är baserad på kinematik. Den föreslagna regleralgoritmen kan balansera den simulerade nedskalade forwardern genom att lösa ett linjärt optimeringsproblem i realtid. Begränsad av sensorprestanda och filteralgoritmer testas endast en förenklad kinematikreglering i simuleringen och i den verkliga nerskalade forwardern. Det kan ses i simulering att både pitch- och roll-vinklar kan minskas kraftigt även med den förenklade reglermetoden vid körning genom Skogforsks standardprovbana. Stabilitetsanalysmetoden för den nedskalade forwardern diskuteras också i denna avhandling. Huvudbidraget från detta examensarbets består i att en annan synvinkel presenterats jämfört med föregående arbeten när det gäller förslag till nya fungerande styrstrategier

Model predictive thermal dose control of a robotic laser system to automate skin photorejuvenation

In this paper, we present a new method to control the thermal stimulation of skin during a photorejuvenation procedure. The proposed method can precisely administer the thermal dose while controlling the tissue’s temperature under a safe limit. For that, a model-based treatment controller is developed and evaluated on a three-dimensional biophysics-based numerical model of skin; A hardware implementation is experimentally tested on a gelatin-based phantom tissue subjected to pulsed laser irradiation. A key component of our method is the use of a new thermal dose metric that enables quantifying and controlling the skin photo-rejuvenation process; This metric represents a suitable alternative to the lack of consensus on the metrics used by the photodermatology community. The reported experiments demonstrate that the developed controller endowed with the proposed dose unit can automatically deliver a prescribed laser irradiation and thermal dose over the tissue surface. The significance of our result is that it provides a control-theoretic framework to automate skin photorejuvenation treatments with thermal-guided robots. This approach has the potential to introduce standards in the automation of these types of photo-treatments

CEPC Technical Design Report -- Accelerator

International audienceThe Circular Electron Positron Collider (CEPC) is a large scientific project initiated and hosted by China, fostered through extensive collaboration with international partners. The complex comprises four accelerators: a 30 GeV Linac, a 1.1 GeV Damping Ring, a Booster capable of achieving energies up to 180 GeV, and a Collider operating at varying energy modes (Z, W, H, and ttbar). The Linac and Damping Ring are situated on the surface, while the Booster and Collider are housed in a 100 km circumference underground tunnel, strategically accommodating future expansion with provisions for a Super Proton Proton Collider (SPPC). The CEPC primarily serves as a Higgs factory. In its baseline design with synchrotron radiation (SR) power of 30 MW per beam, it can achieve a luminosity of 5e34 /cm^2/s^1, resulting in an integrated luminosity of 13 /ab for two interaction points over a decade, producing 2.6 million Higgs bosons. Increasing the SR power to 50 MW per beam expands the CEPC's capability to generate 4.3 million Higgs bosons, facilitating precise measurements of Higgs coupling at sub-percent levels, exceeding the precision expected from the HL-LHC by an order of magnitude. This Technical Design Report (TDR) follows the Preliminary Conceptual Design Report (Pre-CDR, 2015) and the Conceptual Design Report (CDR, 2018), comprehensively detailing the machine's layout and performance, physical design and analysis, technical systems design, R&D and prototyping efforts, and associated civil engineering aspects. Additionally, it includes a cost estimate and a preliminary construction timeline, establishing a framework for forthcoming engineering design phase and site selection procedures. Construction is anticipated to begin around 2027-2028, pending government approval, with an estimated duration of 8 years. The commencement of experiments could potentially initiate in the mid-2030s