Most modern robotic systems are fast and repeatable position controlled machines. However, because of their inability to interact safely, robustly and in a versatile manner, they mostly remain confined to controlled areas where they execute specific preprogrammed actions. Providing high performance motion simultaneously with the ability to physically interact significantly remains a challenge.

Today's robotic systems are mostly rigid and position-controlled machines designed to operate in structured environments. To extend their application domains to partially unknown, dynamic, or anthropic environments, improved physical-interaction capabilities are required. In this new context, to blend the requirements for safety, robustness, and versatility is often a challenge, in part, because commonly available actuator technologies are inadequate. This paper presents our solution with the introduction of the dual-differential rheological actuator (DDRA) concept, which is based on the synergistic combination of an electromagnetic (EM) motor and two differentially coupled magnetorheological (MR) brakes. This paper describes the approach and the prototype design. It then discusses performances in force, motion, and interaction control.

Without a properly designed power management unit, power failures are to be expected on systems raining on batteries. Unfortunately, there is no low cost fully configurable unit that is available on the market for small mobile robots. This paper presents the design of a power management unit for a six legged pneumatic robot that runs at a top speed of 1.11 m/s. The system consists of a main unit that acts as a fast charger, a power supply and a monitor of the energy left available to the robot. This unit communicates with small circuit embedded on each NiMH battery, which gives their level and stores the battery's parameters so that the charger can adapt its charging algorithm to batteries of different capacity or chemistry. Furthermore, this power management unfit takes advantage of the controller area network (CAN) and the PIC18F brain to act as a monitoring, fully configurable, remotely controllable and autonomous node.