Cognitive robotics work makes extensive use of both real world robots and environments, and their simulation equivalents. Simulations are useful in that development time is shorter (or at least has the potential to be), so proof-of-concept experiemnts are readily implemented, and all of the variables are under the control of the designer, allowing better testing and debugging for example. However, from a practical point of view, there are a number of reasons why the use of a physical robotic agent is necessary. Brooks suggested through the “physical grounding hypothesis” [1, 2] that since simulations are by their very nature simplifications of the real world, they miss out details which may be important in terms of complexity of the problem faced by the virtual agent. However, by attempting to implement a high fidelity simulation model, one may use more resources (both human and computational) than by using a real robot – hence defeating the object of using a simulation at all. Related to this, it is also suggested that the designers of the simulation make assumptions as to what is required, thereby unintentionally introducing biases into the model, which would have an effect on the validity of the simulation. An effect of this may be unrealistic behaviours (or ones which would not map to real world behaviour). However, it is acknowledged that when a simulator designed to be independent of any particular theory is used, this last point is effectively rendered void .
In addition to the practical problems outlined in the previous paragraph, there are more philosophical concerns when considering embodiment which will now be briefly stated. The assertion that embodiment is necessary for cognition is now generally accepted, as evidenced by  for example. However the definition of the notion of embodiment is far from clear. Numerous definitions have been used, eight of the most frequently used concepts of which are reviewed by . Among these are general definitions such as embodiment as structural coupling to the environment or as physical instantiation as opposed to software agents (as argued for in the previous paragraph). More restrictive definitions also exist, such as embodiment in an organism-like bodies (which have life-like, but not necessarily alive, bodies), or organismoid embodiment which states that only living bodies allow true embodiment. However, even if the most restrictive definition becomes generally accepted (strong embodiment: that a living body is required), it has been argued that studying 'weakly' embodied systems as if they were strongly embodied would still be a worthwhile research path .
One particularly persuasive argument regarding the essential elements of embodied cognition states that “...the sharing of neural mechanisms between sensorimotor processes and higher-level cognitive processes” is of central importance . This view, which is supported by a wide range of empirical evidence, highlights the necessity of 'low-level' sensory motor contingencies for 'high-level' cognitive processes. In this way, cognition is fundamentally grounded in the sensory and motor capacities of the body in which it is instantiated; cognition can not exist without embodiment – a point emphasized in .
 Brooks, R.A., Elephants don't play chess. Robotics and Autonomous Systems, 1990. 6: p. 3-15.
 Brooks, R.A., Intelligence without Representation. Artificial Intelligence, 1991. 47: p. 139-159.
 Bryson, J., W. Lowe, and L.A. Stein. Hypothesis Testing for Complex Agents. in Proceedings of the NIST Workshop on Performance metrics for intelligent systems. 2000.
 Pfeifer, R. and C. Scheier, Understanding Intelligence. 2001, Cambridge, Massachusetts: MIT Press.
 Ziemke, T. What's that thing called Embodiment? in 25th Annual Meeting of the Cognitive Science Society. 2002. (review)
 Sharkey, N.E. and T. Ziemke, Mechanistic versus Phenomenal embodiment: can robot embodiment lead to strong AI? Journal of Cognitive Systems Research, 2001. 2: p. 251-262. (review)
 Svensson, H. and T. Ziemke. Making sense of Embodiment: simulation theories and the sharing of neural circuitry between sensorimotor and cognitive processes. in 26th Annual Cognitive Science Society Conference. 2004. Chicago, IL.
 Clark, A. and R. Grush, Towards a cognitive robotics. Adaptive Behavior, 1999. 7(1): p. 5-16. (review)