Current neuroscience has identified several constructs to increase the effectiveness of upper extremity rehabilitation. One is the use of progressive, skill acquisition-oriented training. Another approach emphasizes the use of bilateral activities. Building on these principles, this paper describes the design and feasibility testing of a robotic/virtual environment system designed to train the arm of persons who have had strokes. The system provides a variety of assistance modes, scalable workspaces and hand-robot interfaces allowing persons with strokes to train multiple joints in three dimensions. The simulations utilize assistance algorithms that adjust task difficulty both online and offline in relation to subject performance. Several distinctive haptic effects have been incorporated into the simulations. An adaptive master-slave relationship between the unimpaired and impaired arm encourages active movement of the subject's hemiparetic arm during a bimanual task. Adaptive anti-gravity support and damping stabilize the arm during virtual reaching and placement tasks. An adaptive virtual spring provides assistance to complete the movement if the subject is unable to complete the task in time. Finally, haptically rendered virtual objects help to shape the movement trajectory during a virtual placement task. A proof of concept study demonstrated this system to be safe, feasible and worthy of further study.