A Framework of Hybrid Force/Motion Skills Learning for Robots

Human factors and human-centred design philosophy are highly desired in today’s robotics applications such as human-robot interaction (HRI). Several studies showed that endowing robots of human-like interaction skills can not only make them more likeable but also improve their performance. In particular, skill transfer by imitation learning can increase usability and acceptability of robots by the users without computer programming skills. In fact, besides positional information, muscle stiffness of the human arm, contact force with the environment also play important roles in understanding and generating human-like manipulation behaviours for robots, e.g., in physical HRI and tele-operation. To this end, we present a novel robot learning framework based on Dynamic Movement Primitives (DMPs), taking into consideration both the positional and the contact force profiles for human-robot skills transferring. Distinguished from the conventional method involving only the motion information, the proposed framework combines two sets of DMPs, which are built to model the motion trajectory and the force variation of the robot manipulator, respectively. Thus, a hybrid force/motion control approach is taken to ensure the accurate tracking and reproduction of the desired positional and force motor skills. Meanwhile, in order to simplify the control system, a momentum-based force observer is applied to estimate the contact force instead of employing force sensors. To deploy the learned motion-force robot manipulation skills to a broader variety of tasks, the generalization of these DMP models in actual situations is also considered. Comparative experiments have been conducted using a Baxter Robot to verify the effectiveness of the proposed learning framework on real-world scenarios like cleaning a table

A robot learning framework based on adaptive admittance control and generalizable motion modeling with neural network controller

© 2019 Elsevier B.V. Robot learning from demonstration (LfD) enables robots to be fast programmed. This paper presents a novel LfD framework involving a teaching phase, a learning phase and a reproduction phase, and proposes methods in each of these phases to guarantee the overall system performance. An adaptive admittance controller is developed to take into account the unknown human dynamics so that the human tutor can smoothly move the robot around in the teaching phase. The task model in this controller is formulated by the Gaussian mixture regression to extract the human-related motion characteristics. In the learning and reproduction phases, the dynamic movement primitive is employed to model a robotic motion that is generalizable. A neural network-based controller is designed for the robot to track the trajectories generated from the motion model, and a radial basis function neural network is used to compensate for the effect caused by the dynamic environments. Experiments have been performed using a Baxter robot and the results have confirmed the validity of the proposed robot learning framework

Current status of diagnosis and treatment of bladder cancer in China – Analyses of Chinese Bladder Cancer Consortium database

AbstractObjectiveTo investigate current status of diagnosis and treatment of bladder cancer in China.MethodsA database was generated by Chinese Bladder Cancer Consortium (CBCC). From January 2007 to December 2012, 14,260 cases from 44 CBCC centers were included. Data of diagnosis, treatment and pathology were collected.ResultsThe average age was 63.5 year-old and most patients were male (84.3%). The most common histologic types were urothelial carcinoma (91.4%), adenocarcinoma (1.8%), and squamous carcinoma (1.9%). According to 1973 and 2004 WHO grading system, 42.0%, 41.0%, and 17.0% of patients were grade 1, 2, and 3, and 16.0%, 48.7%, and 35.3% of patients were papillary urothelial neoplasms of low malignant potential, low, and high grade, respectively. Non-muscle invasive bladder cancer (NMIBC) and muscle invasive bladder cancer (MIBC) were 25.2% and 74.1%, respectively (0.8% not clear). Carcinoma in situ was only 2.4%. Most patients were diagnosed by white-light cystoscopy with biopsy (74.3%). Fluorescence and narrow band imaging cystoscopy had additional detection rate of 1.0% and 4.0%, respectively. Diagnostic transurethral resection (TUR) provided detection rate of 16.9%. Most NMIBCs were treated with TUR (89.2%). After initial TUR, 2.6% accepted second TUR, and 45.7%, 69.9%, and 58.7% accepted immediate, induced, and maintenance chemotherapy instillation, respectively. Most MIBCs were treated with radical cystectomy (RC, 59.7%). Laparoscopic RCs were 35.1%, while open RC 63.4%. Extended and standard pelvic lymph node dissection were 7% and 66%, respectively. Three most common urinary diversions were orthotopic neobladder (44%), ileal conduit (31%), and ureterocutaneostomy (23%). Only 2.3% of patients accepted neo-adjuvant chemotherapy and only 18% of T3 and T4 patients accepted adjuvant chemotherapy.ConclusionDisease characteristics are similar to international reports, while differences of diagnosis and treatment exist. This study can provide evidences for revisions of the guideline on bladder cancer in China