Interest in telepresence robots is at an all time high, and several companies are already commercializing early or basic versions. There seems to be a huge potential for their use in professional applications, where they can help address some of the challenges companies have found in integrating a geographically distributed work force. However, teleoperation of these robots is typically a difficult task. This difficulty can be attributed to limitations on the information provided to the operator and to communication delay and failures. This may compromise the safety of the people and of the robot during its navigation through the environment. Most commercial systems currently control this risk by reducing size and weight of their robots. Research effort in addressing this problem is generally based on “assisted driving”, which typically adds a “collision avoidance” layer, limiting or avoiding movements that would lead to a collision. In this article, we bring assisted driving to a new level, by introducing concepts from collaborative driving to telepresence robots. More specifically, we use the input from the operator as a general guidance to the target direction, then couple that with a variable degree of autonomy to the robot, depending on the task and the environment. Previous work has shown collision avoidance makes operation easier and reduce the number of collisions. In addition (and in contrast to traditional collision avoidance systems), our approach also reduces the time required to complete a circuit, making navigation easier, safer, and faster. The methodology was evaluated through a controlled user study (N=18). Results show that the use of the proposed collaborative control helped reduce the number of collisions (none in most cases) and also decreased the time to complete the designated task.