This paper investigates how collaborative robots (cobots) can assist a human by mechanically constraining motion to software-defined guide paths, and introduces simple and efficient tools to design ergonomic paths. Analysis of the movements of seven subjects with the Scooter cobot reveals significant differences between guided movements (GM) and free movements (FM). While FM requires learning for each novel task, movements in GM are satisfying from the first trial, require little effort, are faster, smoother, and with fewer back and forth corrections than in FM. Operators rely on path guidance to rotate the Scooter and direct it along curved trajectories. While these advantages demonstrate the strength of the cobot concept, they do not show how guide paths should be defined. We introduce tools to enable the cobot and its operator to collaboratively learn ergonomic guide paths and adapt to changes in the environment. By relying on the haptic sensing, vision, and planning capabilities of the human operator, we can avoid equipping the cobot with complex sensor processing. Experiments with human subjects demonstrate the efficiency and complementarity of these guide paths design tools

Many wheelchair users have problems in orienting themselves and maneuvering the wheelchair in congested environments. Dependent upon others to push them, they can feel powerless. The collaborative wheelchair assistant introduced in this paper may help these people to regain autonomy by providing motion guidance along software-defined paths corresponding to their ability. It enables the user to travel independently, maneuvering round sharp corners and along narrow passages much more easily without compromising speed or safety. This paper investigates the hardware, kinematics and control of the collaborative wheelchair and presents tools by which the user can easily define guiding paths and personalizes the control to a particular disability. The user can also modify the predefined path 'en route' using an elastic path planner, and so escape from danger using reflexes and anticipation. This low cost assistant can be realized on both manual and powered wheelchairs.